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awesome-Federated-Learning
federated-learning
https://github.com/ChanChiChoi/awesome-Federated-Learning
Last synced: 1 day ago
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Uncategorized
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2020
- Federated Composite Optimization
- Federated Unsupervised Representation Learning
- Stochastic Client Selection for Federated Learning with Volatile Clients
- Privacy Leakage of Real-World Vertical Federated Learning
- Asymmetric Private Set Intersection with Applications to Contact Tracing and Private Vertical Federated Machine Learning
- Sliding Differential Evolution Scheduling for Federated Learning in Bandwidth-Limited Networks
- From Distributed Machine Learning To Federated Learning: In The View Of Data Privacy And Security
- A Demonstration of Smart Doorbell Design Using Federated Deep Learning
- Blind Federated Edge Learning
- Feature Inference Attack on Model Predictions in Vertical Federated Learning
- Private Wireless Federated Learning with Anonymous Over-the-Air Computation
- NIPS
- A Federated Learning Approach to Anomaly Detection in Smart Buildings
- Mitigating Sybil Attacks on Differential Privacy based Federated Learning
- GFL: A Decentralized Federated Learning Framework Based On Blockchain
- Differentially-Private Federated Linear Bandits
- Hierarchical Federated Learning through LAN-WAN Orchestration
- NIPS - in-cross-silo-fl](https://github.com/omarfoq/communication-in-cross-silo-fl)]
- Federated Deep Unfolding for Sparse Recovery
- Federated Bandit: A Gossiping Approach
- FedE: Embedding Knowledge Graphs in Federated Setting
- Local Averaging Helps: Hierarchical Federated Learning and Convergence Analysis
- Adaptive Federated Learning and Digital Twin for Industrial Internet of Things
- Federated Learning in Multi-RIS Aided Systems
- Containing Future Epidemics with Trustworthy Federated Systems for Ubiquitous Warning and Response
- Optimal Importance Sampling for Federated Learning
- Optimal Client Sampling for Federated Learning
- Federated Learning From Big Data Over Networks
- Scalable Federated Learning over Passive Optical Networks
- Federated Transfer Learning: concept and applications
- Improving Accuracy of Federated Learning in Non-IID Settings
- Training Speech Recognition Models with Federated Learning: A Quality/Cost Framework
- Flimma: a federated and privacy-preserving tool for differential gene expression analysis
- Semi-supervised Federated Learning for Activity Recognition
- Mitigating Backdoor Attacks in Federated Learning
- An Efficiency-boosting Client Selection Scheme for Federated Learning with Fairness Guarantee
- One-Shot Federated Learning with Neuromorphic Processors
- Federated LQR: Learning through Sharing
- BaFFLe: Backdoor detection via Feedback-based Federated Learning
- Federated Knowledge Distillation
- FederBoost: Private Federated Learning for GBDT
- Collaborative City Digital Twin For Covid-19 Pandemic: A Federated Learning Solution
- FedSL: Federated Split Learning on Distributed Sequential Data in Recurrent Neural Networks
- Resource-Constrained Federated Learning with Heterogeneous Labels and Models
- Federated Crowdsensing: Framework and Challenges
- ASFGNN: Automated Separated-Federated Graph Neural Network
- Adaptive Federated Dropout: Improving Communication Efficiency and Generalization for Federated Learning
- Mitigating Leakage in Federated Learning with Trusted Hardware
- Federated Learning via Intelligent Reflecting Surface
- Privacy Preservation in Federated Learning: Insights from the GDPR Perspective
- Compression Boosts Differentially Private Federated Learning
- Optimized Power Control for Over-the-Air Federated Edge Learning
- A Novel Privacy-Preserved Recommender System Framework based on Federated Learning
- Coded Computing for Low-Latency Federated Learning over Wireless Edge Networks
- Fed-Focal Loss for imbalanced data classification in Federated Learning
- Heterogeneous Data-Aware Federated Learning
- Fast Convergence Algorithm for Analog Federated Learning
- Federated Learning System without Model Sharing through Integration of Dimensional Reduced Data Representations
- An Exploratory Analysis on Users' Contributions in Federated Learning
- Hybrid Federated and Centralized Learning
- Federated Multi-Mini-Batch: An Efficient Training Approach to Federated Learning in Non-IID Environments
- A Theoretical Perspective on Differentially Private Federated Multi-task Learning
- Federated deep reinforcement learning for internet of things with decentralized cooperative edge caching
- FedPerf: A Practitioners’ Guide to Performance of Federated Learning Algorithms
- ICML - a-communicationefficient-algorithm-for-federated-learning](https://slideslive.com/38928463/fedboost-a-communicationefficient-algorithm-for-federated-learning?ref=speaker-16993-latest)]
- NIPS
- NIPS
- NIPS
- NIPS
- NIPS - AI/FedML/tree/master/fedml_experiments/distributed/fedgkt](https://github.com/FedML-AI/FedML/tree/master/fedml_experiments/distributed/fedgkt)]
- NIPS
- NIPS
- NIPS
- NIPS
- NIPS
- NIPS
- Secure multiparty computations in floating-point arithmetic
- Self Organization Agent Oriented Dynamic Resource Allocation on Open Federated Clouds Environment
- A Federated Learning Framework for Privacy-preserving and Parallel Training
- Prophet: Proactive Candidate-Selection for Federated Learning by Predicting the Qualities of Training and Reporting Phases
- Federated Learning under Channel Uncertainty: Joint Client Scheduling and Resource Allocation
- Federated Orchestration for Network Slicing of Bandwidth and Computational Resource
- The Sum of Its Parts: Analysis of Federated Byzantine Agreement Systems
- Optimizing Federated Queries Based on the Physical Design of a Data Lake
- Bringing Inter-Thread Cache Benefits to Federated Scheduling -- Extended Results & Technical Report
- CatFedAvg: Optimising Communication-efficiency and Classification Accuracy in Federated Learning
- FedRec: Federated Learning of Universal Receivers over Fading Channels
- End-to-End Evaluation of Federated Learning and Split Learning for Internet of Things
- CPFed: Communication-Efficient and Privacy-Preserving Federated Learning
- Second-Order Guarantees in Centralized, Federated and Decentralized Nonconvex Optimization
- DataFed: Towards Reproducible Research via Federated Data Management
- funcX: A Federated Function Serving Fabric for Science
- Intracranial Hemorrhage Detection Using Neural Network Based Methods With Federated Learning
- Reliability and Performance Assessment of Federated Learning on Clinical Benchmark Data
- Responsive Web User Interface to Recover Training Data from User Gradients in Federated Learning
- NIPS
- A Unified Analysis of Stochastic Gradient Methods for Nonconvex Federated Optimization
- FedGAN: Federated Generative Adversarial Networks for Distributed Data
- Free-rider Attacks on Model Aggregation in Federated Learning
- Harnessing Wireless Channels for Scalable and Privacy-Preserving Federated Learning
- Multi-Armed Bandit Based Client Scheduling for Federated Learning
- Coded Computing for Federated Learning at the Edge
- Delay Minimization for Federated Learning Over Wireless Communication Networks
- A Federated F-score Based Ensemble Model for Automatic Rule Extraction
- Defending Against Backdoors in Federated Learning with Robust Learning Rate
- Personalized Federated Learning: An Attentive Collaboration Approach
- BlockFLow: An Accountable and Privacy-Preserving Solution for Federated Learning
- Federated Learning of User Authentication Models
- Differentially private cross-silo federated learning
- Experiments of Federated Learning for COVID-19 Chest X-ray Images
- Federated Learning's Blessing: FedAvg has Linear Speedup
- Joint Auction-Coalition Formation Framework for Communication-Efficient Federated Learning in UAV-Enabled Internet of Vehicles
- Blockchain-Federated-Learning and Deep Learning Models for COVID-19 detection using CT Imaging
- Joint Device Scheduling and Resource Allocation for Latency Constrained Wireless Federated Learning
- Privacy Preserving Text Recognition with Gradient-Boosting for Federated Learning
- ICML - communicationefficient-federated-learning-with-sketching](https://slideslive.com/38928454/fetchsgd-communicationefficient-federated-learning-with-sketching)]
- Federated Learning in Mobile Edge Computing: An Edge-Learning Perspective for Beyond 5G
- Less is More: A privacy-respecting Android malware classifier using Federated Learning
- Data Poisoning Attacks Against Federated Learning Systems
- Prioritized Multi-Criteria Federated Learning
- Asynchronous Federated Learning with Reduced Number of Rounds and with Differential Privacy from Less Aggregated Gaussian Noise
- User-Oriented Multi-Task Federated Deep Learning for Mobile Edge Computing
- Multi-Stage Hybrid Federated Learning over Large-Scale Wireless Fog Networks
- Deep Anomaly Detection for Time-series Data in Industrial IoT: A Communication-Efficient On-device Federated Learning Approach
- FPGA-Based Hardware Accelerator of Homomorphic Encryption for Efficient Federated Learning
- Incentives for Federated Learning: a Hypothesis Elicitation Approach
- IBM Federated Learning: an Enterprise Framework White Paper V0.1
- Byzantine-Resilient Secure Federated Learning
- FedOCR: Communication-Efficient Federated Learning for Scene Text Recognition
- Federated Learning in the Sky: Aerial-Ground Air Quality Sensing Framework with UAV Swarms
- FedCTR: Federated Native Ad CTR Prediction with Multi-Platform User Behavior Data
- Federated Self-Supervised Learning of Multi-Sensor Representations for Embedded Intelligence
- Empowering the Edge Intelligence by Air-Ground Integrated Federated Learning in 6G Networks
- Fast-Convergent Federated Learning
- FedEmail: Performance Measurement of Privacy-friendly Phishing Detection Enabled by Federated Learning
- VFL: A Verifiable Federated Learning with Privacy-Preserving for Big Data in Industrial IoT
- Fully Decentralized Federated Learning Based Beamforming Design for UAV Communications
- Accelerating Federated Learning over Reliability-Agnostic Clients in Mobile Edge Computing Systems
- SAFER: Sparse Secure Aggregation for Federated Learning
- Cluster-Based Cooperative Digital Over-the-Air Aggregation for Wireless Federated Edge Learning
- Sparsified Privacy-Masking for Communication-Efficient and Privacy-Preserving Federated Learning
- Federated Transfer Learning with Dynamic Gradient Aggregation
- On the relationship between (secure) multi-party computation and (secure) federated learning
- Improving on-device speaker verification using federated learning with privacy
- LotteryFL: Personalized and Communication-Efficient Federated Learning with Lottery Ticket Hypothesis on Non-IID Datasets
- Mime: Mimicking Centralized Stochastic Algorithms in Federated Learning
- SplitNN-driven vertical partitioning
- Federated Learning via Synthetic Data
- FedNNNN: Norm-Normalized Neural Network Aggregation for Fast and Accurate Federated Learning
- Holdout SGD: Byzantine Tolerant Federated Learning
- Scalable and Communication-efficient Decentralized Federated Edge Learning with Multi-blockchain Framework
- FedSKETCH: Communication-Efficient and Private Federated Learning via Sketching
- Distantly Supervised Relation Extraction in Federated Settings
- Dispersed Federated Learning: Vision, Taxonomy, and Future Directions
- WAFFLe: Weight Anonymized Factorization for Federated Learning
- Privacy Preserving Vertical Federated Learning for Tree-based Models
- Distillation-Based Semi-Supervised Federated Learning for Communication-Efficient Collaborative Training with Non-IID Private Data
- Federated Doubly Stochastic Kernel Learning for Vertically Partitioned Data
- Towards Class Imbalance in Federated Learning
- Privacy-Preserving Asynchronous Federated Learning Algorithms for Multi-Party Vertically Collaborative Learning
- A VCG-based Fair Incentive Mechanism for Federated Learning
- Heterogeneous Federated Learning
- Shuffled Model of Federated Learning: Privacy, Communication and Accuracy Trade-offs
- How to Put Users in Control of their Data via Federated Pair-Wise Recommendation
- An Isolated Data Island Benchmark Suite for Federated Learning
- WAFFLE: Watermarking in Federated Learning
- Siloed Federated Learning for Multi-Centric Histopathology Datasets
- Information-Theoretic Privacy in Federated Submodel learning
- MICCAIW
- Toward Smart Security Enhancement of Federated Learning Networks
- Federated Learning with Communication Delay in Edge Networks
- Federated Learning for Cellular-connected UAVs: Radio Mapping and Path Planning
- A Federated Multi-View Deep Learning Framework for Privacy-Preserving Recommendations
- FedMVT: Semi-supervised Vertical Federated Learning with MultiView Training
- Federated Learning for Channel Estimation in Conventional and IRS-Assisted Massive MIMO
- Convergence of Federated Learning over a Noisy Downlink
- Accelerating Federated Learning in Heterogeneous Data and Computational Environments
- Benchmarking Semi-supervised Federated Learning
- GraphFederator: Federated Visual Analysis for Multi-party Graphs
- Collaborative Fairness in Federated Learning
- A Federated Approach for Fine-Grained Classification of Fashion Apparel
- GRAFFL: Gradient-free Federated Learning of a Bayesian Generative Model
- Federated Edge Learning : Design Issues and Challenges
- POSEIDON: Privacy-Preserving Federated Neural Network Learning
- Fed-Sim: Federated Simulation for Medical Imaging
- ESMFL: Efficient and Secure Models for Federated Learning
- Federated Learning for Breast Density Classification: A Real-World Implementation
- FedDistill: Making Bayesian Model Ensemble Applicable to Federated Learning
- User Selection Approaches to Mitigate the Straggler Effect for Federated Learning on Cell-Free Massive MIMO Networks
- FLFE: A Communication-Efficient and Privacy-Preserving Federated Feature Engineering Framework
- Particle Swarm Optimized Federated Learning For Industrial IoT and Smart City Services
- Blockchain-based Federated Learning for Failure Detection in Industrial IoT
- Hybrid Differentially Private Federated Learning on Vertically Partitioned Data
- A Real-time Contribution Measurement Method for Participants in Federated Learning
- Toward Robustness and Privacy in Federated Learning: Experimenting with Local and Central Differential Privacy
- Federated Classification using Parsimonious Functions in Reproducing Kernel Hilbert Spaces
- Federated Model Distillation with Noise-Free Differential Privacy
- Trading Data For Learning: Incentive Mechanism For On-Device Federated Learning
- FLaPS: Federated Learning and Privately Scaling
- A Principled Approach to Data Valuation for Federated Learning
- A Vertical Federated Learning Method for Interpretable Scorecard and Its Application in Credit Scoring
- Fed+: A Family of Fusion Algorithms for Federated Learning
- Federated Generalized Bayesian Learning via Distributed Stein Variational Gradient Descent
- Effective Federated Adaptive Gradient Methods with Non-IID Decentralized Data
- FedSmart: An Auto Updating Federated Learning Optimization Mechanism
- Distilled One-Shot Federated Learning
- FLAME: Differentially Private Federated Learning in the Shuffle Model
- Byzantine-Robust Variance-Reduced Federated Learning over Distributed Non-i.i.d. Data
- Robust Aggregation for Adaptive Privacy Preserving Federated Learning in Healthcare
- Federated Learning with Nesterov Accelerated Gradient Momentum Method
- When Federated Learning Meets Blockchain: A New Distributed Learning Paradigm
- Estimation of Individual Device Contributions for Incentivizing Federated Learning
- Connecting Distributed Pockets of EnergyFlexibility through Federated Computations:Limitations and Possibilities
- Federated Learning for Computational Pathology on Gigapixel Whole Slide Images
- An Incentive Mechanism for Federated Learning in Wireless Cellular network: An Auction Approach
- Dynamic Fusion based Federated Learning for COVID-19 Detection
- When Deep Reinforcement Learning Meets Federated Learning: Intelligent Multi-Timescale Resource Management for Multi-access Edge Computing in 5G Ultra Dense Network
- FedCluster: Boosting the Convergence of Federated Learning via Cluster-Cycling
- Pocket Diagnosis: Secure Federated Learning against Poisoning Attack in the Cloud
- FastSecAgg: Scalable Secure Aggregation for Privacy-Preserving Federated Learning
- Over-the-Air Federated Learning from Heterogeneous Data
- Loosely Coupled Federated Learning Over Generative Models
- Federated Learning for Internet of Things: Recent Advances, Taxonomy, and Open Challenges
- MAB-based Client Selection for Federated Learning with Uncertain Resources in Mobile Networks
- Secure Aggregation with Heterogeneous Quantization in Federated Learning
- Optimal Task Assignment to Heterogeneous Federated Learning Devices
- Model-sharing Games: Analyzing Federated Learning Under Voluntary Participation
- Model-Agnostic Round-Optimal Federated Learning via Knowledge Transfer
- $X$-Secure $T$-Private Federated Submodel Learning
- Client Selection in Federated Learning: Convergence Analysis and Power-of-Choice Selection Strategies
- HeteroFL: Computation and Communication Efficient Federated Learning for Heterogeneous Clients
- Federated learning using a mixture of experts
- NIPS
- Optimal Gradient Compression for Distributed and Federated Learning
- Voting-based Approaches For Differentially Private Federated Learning
- Fairness-aware Agnostic Federated Learning
- Federated Learning via Posterior Averaging: A New Perspective and Practical Algorithms
- Differentially Private Secure Multi-Party Computation for Federated Learning in Financial Applications
- FedAT: A Communication-Efficient Federated Learning Method with Asynchronous Tiers under Non-IID Data
- Oort: Informed Participant Selection for Scalable Federated Learning
- COVID-19 Imaging Data Privacy by Federated Learning Design: A Theoretical Framework
- A first look into the carbon footprint of federated learning
- FedGroup: Ternary Cosine Similarity-based Clustered Federated Learning Framework toward High Accuracy in Heterogeneous Data
- BlockFLA: Accountable Federated Learning via Hybrid Blockchain Architecture
- Mitigating Byzantine Attacks in Federated Learning
- Federated Learning in Adversarial Settings
- Federated TON_IoT Windows Datasets for Evaluating AI-based Security Applications
- Flow-FL: Data-Driven Federated Learning for Spatio-Temporal Predictions in Multi-Robot Systems
- Secure Weighted Aggregation in Federated Learning
- Layer-wise Characterization of Latent Information Leakage in Federated Learning
- FLaaS: Federated Learning as a Service
- FedEval: A Benchmark System with a Comprehensive Evaluation Model for Federated Learning
- Budgeted Online Selection of Candidate IoT Clients to Participate in Federated Learning
- Low-latency Federated Learning and Blockchain for Edge Association in Digital Twin empowered 6G Networks
- Dynamic backdoor attacks against federated learning
- 2CP: Decentralized Protocols to Transparently Evaluate Contributivity in Blockchain Federated Learning Environments
- Reconfigurable Intelligent Surface Enabled Federated Learning: A Unified Communication-Learning Design Approach
- Towards Building a Robust and Fair Federated Learning System
- LINDT: Tackling Negative Federated Learning with Local Adaptation
- Federated learning with class imbalance reduction
- Improving Federated Relational Data Modeling via Basis Alignment and Weight Penalty
- Federated Semi-Supervised Learning for COVID Region Segmentation in Chest CT using Multi-National Data from China, Italy, Japan
- Toward Multiple Federated Learning Services Resource Sharing in Mobile Edge Networks
- MetaGater: Fast Learning of Conditional Channel Gated Networks via Federated Meta-Learning
- Distributed Additive Encryption and Quantization for Privacy Preserving Federated Deep Learning
- Optimizing Resource-Efficiency for Federated Edge Intelligence in IoT Networks
- Privacy-Preserving Federated Learning for UAV-Enabled Networks: Learning-Based Joint Scheduling and Resource Management
- Advancements of federated learning towards privacy preservation: from federated learning to split learning
- ??
- Communication-Efficient Federated Distillation
- Fast-Convergent Federated Learning with Adaptive Weighting
- MYSTIKO : : Cloud-Mediated, Private, Federated Gradient Descent
- Federated Marginal Personalization for ASR Rescoring
- Second-Order Guarantees in Federated Learning
- Federated Learning with Diversified Preference for Humor Recognition
- Robust Federated Learning with Noisy Labels
- FAT: Federated Adversarial Training
- A Systematic Literature Review on Federated Learning: From A Model Quality Perspective
- Blockchain Assisted Decentralized Federated Learning (BLADE-FL) with Lazy Clients
- Mitigating Bias in Federated Learning
- Federated Learning with Heterogeneous Labels and Models for Mobile Activity Monitoring
- Probabilistic Federated Learning of Neural Networks Incorporated with Global Posterior Information
- TornadoAggregate: Accurate and Scalable Federated Learning via the Ring-Based Architecture
- Accurate and Fast Federated Learning via Combinatorial Multi-Armed Bandits
- FedSemi: An Adaptive Federated Semi-Supervised Learning Framework
- Vehicular Cooperative Perception Through Action Branching and Federated Reinforcement Learning
- Dynamic Clustering in Federated Learning
- Design and Analysis of Uplink and Downlink Communications for Federated Learning
- Improved Convergence Rates for Non-Convex Federated Learning with Compression
- GraphFL: A Federated Learning Framework for Semi-Supervised Node Classification on Graphs
- Federated Multi-Task Learning for Competing Constraints
- RC-SSFL: Towards Robust and Communication-efficient Semi-supervised Federated Learning System
- Towards Communication-efficient and Attack-Resistant Federated Edge Learning for Industrial Internet of Things
- Accurate and Fast Federated Learning via IID and Communication-Aware Grouping
- Federated Learning in Unreliable and Resource-Constrained Cellular Wireless Networks
- Communication-Computation Efficient Secure Aggregation for Federated Learning
- Analysis and Optimal Edge Assignment For Hierarchical Federated Learning on Non-IID Data
- DONE: Distributed Newton-type Method for Federated Edge Learning
- Provable Defense against Privacy Leakage in Federated Learning from Representation Perspective
- FLEAM: A Federated Learning Empowered Architecture to Mitigate DDoS in Industrial IoT
- Privacy and Robustness in Federated Learning: Attacks and Defenses
- Adaptive Histogram-Based Gradient Boosted Trees for Federated Learning
- Communication-Efficient Federated Learning with Compensated Overlap-FedAvg
- Federated learning in vehicular edge computing: A selective model aggregation approach - 23935.
- Achieving Security and Privacy in Federated Learning Systems: Survey, Research Challenges and Future Directions
- Age-Optimal Power Allocation in Industrial IoT: A Risk-Sensitive Federated Learning Approach
- Federated Mimic Learning for Privacy Preserving Intrusion Detection
- Privacy-preserving Decentralized Aggregation for Federated Learning
- Federated Learning under Importance Sampling
- FedHome: Cloud-Edge based Personalized Federated Learning for In-Home Health Monitoring
- Bandit-based Communication-Efficient Client Selection Strategies for Federated Learning
- CosSGD: Nonlinear Quantization for Communication-efficient Federated Learning
- Cost-Effective Federated Learning Design
- Personalized Federated Learning with First Order Model Optimization
- Inexact-ADMM Based Federated Meta-Learning for Fast and Continual Edge Learning
- More Industry-friendly: Federated Learning with High Efficient Design
- FedADC: Accelerated Federated Learning with Drift Control
- Fairness and Accuracy in Federated Learning
- GDPR-inspired IoT Ontology enabling Semantic Interoperability, Federation of Deployments and Privacy-Preserving Applications
- FedServing: A Federated Prediction Serving Framework Based on Incentive Mechanism
- Toward Understanding the Influence of Individual Clients in Federated Learning
- To Talk or to Work: Energy Efficient Federated Learning over Mobile Devices via the Weight Quantization and 5G Transmission Co-Design
- FedeRank: User Controlled Feedback with Federated Recommender Systems
- To Talk or to Work: Flexible Communication Compression for Energy Efficient Federated Learning over Heterogeneous Mobile Edge Devices
- Turn Signal Prediction: A Federated Learning Case Study
- Hybrid Federated Learning: Algorithms and Implementation
- Decentralized Federated Learning via Mutual Knowledge Transfer
- Federated Unlearning
- Federated Block Coordinate Descent Scheme for Learning Global and Personalized Models
- FLTrust: Byzantine-robust Federated Learning via Trust Bootstrapping
- Federated Multi-Agent Actor-Critic Learning for Age Sensitive Mobile Edge Computing
- Straggler-Resilient Federated Learning: Leveraging the Interplay Between Statistical Accuracy and System Heterogeneity
- Bayesian Federated Learning over Wireless Networks
- PFL-MoE: Personalized Federated Learning Based on Mixture of Experts
- Timely Communication in Federated Learning
- FedEmail: Performance Measurement of Privacy-friendly Phishing Detection Enabled by Federated Learning
- Heterogeneous Federated Learning
- Fed-Sim: Federated Simulation for Medical Imaging
- NIPS - in-cross-silo-fl](https://github.com/omarfoq/communication-in-cross-silo-fl)]
- FedEval: A Benchmark System with a Comprehensive Evaluation Model for Federated Learning
- DONE: Distributed Newton-type Method for Federated Edge Learning
- Inexact-ADMM Based Federated Meta-Learning for Fast and Continual Edge Learning
- Decentralized Federated Learning via Mutual Knowledge Transfer
- ICML - communicationefficient-federated-learning-with-sketching](https://slideslive.com/38928454/fetchsgd-communicationefficient-federated-learning-with-sketching)]
- Data Poisoning Attacks Against Federated Learning Systems
- User-Oriented Multi-Task Federated Deep Learning for Mobile Edge Computing
- Incentives for Federated Learning: a Hypothesis Elicitation Approach
- IBM Federated Learning: an Enterprise Framework White Paper V0.1
- Byzantine-Resilient Secure Federated Learning
- A Systematic Literature Review on Federated Machine Learning: From A Software Engineering Perspective
- Empowering the Edge Intelligence by Air-Ground Integrated Federated Learning in 6G Networks
- Self Organization Agent Oriented Dynamic Resource Allocation on Open Federated Clouds Environment
- A Federated Learning Framework for Privacy-preserving and Parallel Training
- Prophet: Proactive Candidate-Selection for Federated Learning by Predicting the Qualities of Training and Reporting Phases
- Federated Learning under Channel Uncertainty: Joint Client Scheduling and Resource Allocation
- The Sum of Its Parts: Analysis of Federated Byzantine Agreement Systems
- Optimizing Federated Queries Based on the Physical Design of a Data Lake
- DataFed: Towards Reproducible Research via Federated Data Management
- CPFed: Communication-Efficient and Privacy-Preserving Federated Learning
- Intracranial Hemorrhage Detection Using Neural Network Based Methods With Federated Learning
- Reliability and Performance Assessment of Federated Learning on Clinical Benchmark Data
- Responsive Web User Interface to Recover Training Data from User Gradients in Federated Learning
- NIPS
- A Unified Analysis of Stochastic Gradient Methods for Nonconvex Federated Optimization
- Free-rider Attacks on Model Aggregation in Federated Learning
- Accelerating Federated Learning over Reliability-Agnostic Clients in Mobile Edge Computing Systems
- Cluster-Based Cooperative Digital Over-the-Air Aggregation for Wireless Federated Edge Learning
- Sparsified Privacy-Masking for Communication-Efficient and Privacy-Preserving Federated Learning
- Federated Transfer Learning with Dynamic Gradient Aggregation
- Fully Decentralized Federated Learning Based Beamforming Design for UAV Communications
- Delay Minimization for Federated Learning Over Wireless Communication Networks
- A Federated F-score Based Ensemble Model for Automatic Rule Extraction
- Defending Against Backdoors in Federated Learning with Robust Learning Rate
- Personalized Federated Learning: An Attentive Collaboration Approach
- BlockFLow: An Accountable and Privacy-Preserving Solution for Federated Learning
- Federated Learning of User Authentication Models
- Differentially private cross-silo federated learning
- Federated Learning's Blessing: FedAvg has Linear Speedup
- Harnessing Wireless Channels for Scalable and Privacy-Preserving Federated Learning
- Multi-Armed Bandit Based Client Scheduling for Federated Learning
- Coded Computing for Federated Learning at the Edge
- The Good, The Bad, and The Ugly: Quality Inference in Federated Learning
- Blockchain-Federated-Learning and Deep Learning Models for COVID-19 detection using CT Imaging
- Energy-Efficient Resource Management for Federated Edge Learning with CPU-GPU Heterogeneous Computing
- Joint Device Scheduling and Resource Allocation for Latency Constrained Wireless Federated Learning
- Privacy Preserving Text Recognition with Gradient-Boosting for Federated Learning
- Federated Learning in Mobile Edge Computing: An Edge-Learning Perspective for Beyond 5G
- Less is More: A privacy-respecting Android malware classifier using Federated Learning
- NIPS
- NIPS
- On the relationship between (secure) multi-party computation and (secure) federated learning
- Improving on-device speaker verification using federated learning with privacy
- LotteryFL: Personalized and Communication-Efficient Federated Learning with Lottery Ticket Hypothesis on Non-IID Datasets
- Mime: Mimicking Centralized Stochastic Algorithms in Federated Learning
- Federated Learning via Synthetic Data
- FedNNNN: Norm-Normalized Neural Network Aggregation for Fast and Accurate Federated Learning
- Holdout SGD: Byzantine Tolerant Federated Learning
- FedSKETCH: Communication-Efficient and Private Federated Learning via Sketching
- Distantly Supervised Relation Extraction in Federated Settings
- Privacy Preserving Vertical Federated Learning for Tree-based Models
- Privacy-Preserving Asynchronous Federated Learning Algorithms for Multi-Party Vertically Collaborative Learning
- Siloed Federated Learning for Multi-Centric Histopathology Datasets
- Information-Theoretic Privacy in Federated Submodel learning
- Federated Learning with Communication Delay in Edge Networks
- Federated Learning for Cellular-connected UAVs: Radio Mapping and Path Planning
- FedMVT: Semi-supervised Vertical Federated Learning with MultiView Training
- Federated Learning for Channel Estimation in Conventional and IRS-Assisted Massive MIMO
- Convergence of Federated Learning over a Noisy Downlink
- Collaborative Fairness in Federated Learning
- A Federated Approach for Fine-Grained Classification of Fashion Apparel
- GRAFFL: Gradient-free Federated Learning of a Bayesian Generative Model
- Federated Edge Learning : Design Issues and Challenges
- User Selection Approaches to Mitigate the Straggler Effect for Federated Learning on Cell-Free Massive MIMO Networks
- FLFE: A Communication-Efficient and Privacy-Preserving Federated Feature Engineering Framework
- Particle Swarm Optimized Federated Learning For Industrial IoT and Smart City Services
- Hybrid Differentially Private Federated Learning on Vertically Partitioned Data
- Toward Robustness and Privacy in Federated Learning: Experimenting with Local and Central Differential Privacy
- Federated Classification using Parsimonious Functions in Reproducing Kernel Hilbert Spaces
- Federated Model Distillation with Noise-Free Differential Privacy
- Trading Data For Learning: Incentive Mechanism For On-Device Federated Learning
- FLaPS: Federated Learning and Privately Scaling
- Federated Generalized Bayesian Learning via Distributed Stein Variational Gradient Descent
- FedSmart: An Auto Updating Federated Learning Optimization Mechanism
- Distilled One-Shot Federated Learning
- Federated Learning with Nesterov Accelerated Gradient Momentum Method
- When Federated Learning Meets Blockchain: A New Distributed Learning Paradigm
- Connecting Distributed Pockets of EnergyFlexibility through Federated Computations:Limitations and Possibilities
- FedCluster: Boosting the Convergence of Federated Learning via Cluster-Cycling
- FastSecAgg: Scalable Secure Aggregation for Privacy-Preserving Federated Learning
- Over-the-Air Federated Learning from Heterogeneous Data
- Loosely Coupled Federated Learning Over Generative Models
- MAB-based Client Selection for Federated Learning with Uncertain Resources in Mobile Networks
- Optimal Task Assignment to Heterogeneous Federated Learning Devices
- Model-sharing Games: Analyzing Federated Learning Under Voluntary Participation
- Model-Agnostic Round-Optimal Federated Learning via Knowledge Transfer
- $X$-Secure $T$-Private Federated Submodel Learning
- Client Selection in Federated Learning: Convergence Analysis and Power-of-Choice Selection Strategies
- Federated learning using a mixture of experts
- NIPS
- Optimal Gradient Compression for Distributed and Federated Learning
- Voting-based Approaches For Differentially Private Federated Learning
- Differentially Private Secure Multi-Party Computation for Federated Learning in Financial Applications
- COVID-19 Imaging Data Privacy by Federated Learning Design: A Theoretical Framework
- A first look into the carbon footprint of federated learning
- FedGroup: Ternary Cosine Similarity-based Clustered Federated Learning Framework toward High Accuracy in Heterogeneous Data
- Mitigating Byzantine Attacks in Federated Learning
- Federated Learning in Adversarial Settings
- Federated TON_IoT Windows Datasets for Evaluating AI-based Security Applications
- Flow-FL: Data-Driven Federated Learning for Spatio-Temporal Predictions in Multi-Robot Systems
- Secure Weighted Aggregation in Federated Learning
- Layer-wise Characterization of Latent Information Leakage in Federated Learning
- Federated Unsupervised Representation Learning
- Sliding Differential Evolution Scheduling for Federated Learning in Bandwidth-Limited Networks
- From Distributed Machine Learning To Federated Learning: In The View Of Data Privacy And Security
- A Demonstration of Smart Doorbell Design Using Federated Deep Learning
- Blind Federated Edge Learning
- Feature Inference Attack on Model Predictions in Vertical Federated Learning
- Mitigating Sybil Attacks on Differential Privacy based Federated Learning
- GFL: A Decentralized Federated Learning Framework Based On Blockchain
- Differentially-Private Federated Linear Bandits
- Hierarchical Federated Learning through LAN-WAN Orchestration
- Federated Bandit: A Gossiping Approach
- FedE: Embedding Knowledge Graphs in Federated Setting
- Federated Learning in Multi-RIS Aided Systems
- Optimal Importance Sampling for Federated Learning
- Optimal Client Sampling for Federated Learning
- Federated Learning From Big Data Over Networks
- Scalable Federated Learning over Passive Optical Networks
- Federated Transfer Learning: concept and applications
- Improving Accuracy of Federated Learning in Non-IID Settings
- Training Speech Recognition Models with Federated Learning: A Quality/Cost Framework
- Flimma: a federated and privacy-preserving tool for differential gene expression analysis
- Mitigating Backdoor Attacks in Federated Learning
- An Efficiency-boosting Client Selection Scheme for Federated Learning with Fairness Guarantee
- One-Shot Federated Learning with Neuromorphic Processors
- Federated LQR: Learning through Sharing
- BaFFLe: Backdoor detection via Feedback-based Federated Learning
- FederBoost: Private Federated Learning for GBDT
- Collaborative City Digital Twin For Covid-19 Pandemic: A Federated Learning Solution
- Resource-Constrained Federated Learning with Heterogeneous Labels and Models
- Federated Crowdsensing: Framework and Challenges
- ASFGNN: Automated Separated-Federated Graph Neural Network
- Adaptive Federated Dropout: Improving Communication Efficiency and Generalization for Federated Learning
- Mitigating Leakage in Federated Learning with Trusted Hardware
- Federated Learning via Intelligent Reflecting Surface
- Compression Boosts Differentially Private Federated Learning
- Coded Computing for Low-Latency Federated Learning over Wireless Edge Networks
- Fed-Focal Loss for imbalanced data classification in Federated Learning
- Heterogeneous Data-Aware Federated Learning
- Fast Convergence Algorithm for Analog Federated Learning
- Federated Learning System without Model Sharing through Integration of Dimensional Reduced Data Representations
- Hybrid Federated and Centralized Learning
- Federated Multi-Mini-Batch: An Efficient Training Approach to Federated Learning in Non-IID Environments
- A Theoretical Perspective on Differentially Private Federated Multi-task Learning
- CatFedAvg: Optimising Communication-efficiency and Classification Accuracy in Federated Learning
- FedRec: Federated Learning of Universal Receivers over Fading Channels
- Dynamic backdoor attacks against federated learning
- 2CP: Decentralized Protocols to Transparently Evaluate Contributivity in Blockchain Federated Learning Environments
- Federated Composite Optimization
- Private Wireless Federated Learning with Anonymous Over-the-Air Computation
- Stochastic Client Selection for Federated Learning with Volatile Clients
- Privacy Leakage of Real-World Vertical Federated Learning
- Asymmetric Private Set Intersection with Applications to Contact Tracing and Private Vertical Federated Machine Learning
- Budgeted Online Selection of Candidate IoT Clients to Participate in Federated Learning
- Reconfigurable Intelligent Surface Enabled Federated Learning: A Unified Communication-Learning Design Approach
- Towards Building a Robust and Fair Federated Learning System
- Federated learning with class imbalance reduction
- Improving Federated Relational Data Modeling via Basis Alignment and Weight Penalty
- Federated Semi-Supervised Learning for COVID Region Segmentation in Chest CT using Multi-National Data from China, Italy, Japan
- MetaGater: Fast Learning of Conditional Channel Gated Networks via Federated Meta-Learning
- Distributed Additive Encryption and Quantization for Privacy Preserving Federated Deep Learning
- Optimizing Resource-Efficiency for Federated Edge Intelligence in IoT Networks
- Advancements of federated learning towards privacy preservation: from federated learning to split learning
- Communication-Efficient Federated Distillation
- Fast-Convergent Federated Learning with Adaptive Weighting
- MYSTIKO : : Cloud-Mediated, Private, Federated Gradient Descent
- Federated Marginal Personalization for ASR Rescoring
- Second-Order Guarantees in Federated Learning
- FAT: Federated Adversarial Training
- Blockchain Assisted Decentralized Federated Learning (BLADE-FL) with Lazy Clients
- Mitigating Bias in Federated Learning
- Federated Learning with Heterogeneous Labels and Models for Mobile Activity Monitoring
- Probabilistic Federated Learning of Neural Networks Incorporated with Global Posterior Information
- TornadoAggregate: Accurate and Scalable Federated Learning via the Ring-Based Architecture
- Accurate and Fast Federated Learning via Combinatorial Multi-Armed Bandits
- FedSemi: An Adaptive Federated Semi-Supervised Learning Framework
- Dynamic Clustering in Federated Learning
- GraphFL: A Federated Learning Framework for Semi-Supervised Node Classification on Graphs
- RC-SSFL: Towards Robust and Communication-efficient Semi-supervised Federated Learning System
- Communication-Computation Efficient Secure Aggregation for Federated Learning
- FLEAM: A Federated Learning Empowered Architecture to Mitigate DDoS in Industrial IoT
- Adaptive Histogram-Based Gradient Boosted Trees for Federated Learning
- Achieving Security and Privacy in Federated Learning Systems: Survey, Research Challenges and Future Directions
- Age-Optimal Power Allocation in Industrial IoT: A Risk-Sensitive Federated Learning Approach
- Federated Mimic Learning for Privacy Preserving Intrusion Detection
- Privacy-preserving Decentralized Aggregation for Federated Learning
- Federated Learning under Importance Sampling
- FedHome: Cloud-Edge based Personalized Federated Learning for In-Home Health Monitoring
- Bandit-based Communication-Efficient Client Selection Strategies for Federated Learning
- CosSGD: Nonlinear Quantization for Communication-efficient Federated Learning
- More Industry-friendly: Federated Learning with High Efficient Design
- Fairness and Accuracy in Federated Learning
- GDPR-inspired IoT Ontology enabling Semantic Interoperability, Federation of Deployments and Privacy-Preserving Applications
- FedServing: A Federated Prediction Serving Framework Based on Incentive Mechanism
- FedeRank: User Controlled Feedback with Federated Recommender Systems
- To Talk or to Work: Flexible Communication Compression for Energy Efficient Federated Learning over Heterogeneous Mobile Edge Devices
- Hybrid Federated Learning: Algorithms and Implementation
- FLTrust: Byzantine-robust Federated Learning via Trust Bootstrapping
- Federated Multi-Agent Actor-Critic Learning for Age Sensitive Mobile Edge Computing
- PFL-MoE: Personalized Federated Learning Based on Mixture of Experts
- Timely Communication in Federated Learning
- Federated learning in vehicular edge computing: A selective model aggregation approach - 23935.
- Federated Orchestration for Network Slicing of Bandwidth and Computational Resource
- FedGAN: Federated Generative Adversarial Networks for Distributed Data
- Bringing Inter-Thread Cache Benefits to Federated Scheduling -- Extended Results & Technical Report
- Robust Aggregation for Adaptive Privacy Preserving Federated Learning in Healthcare
- funcX: A Federated Function Serving Fabric for Science
- NIPS
- Joint Auction-Coalition Formation Framework for Communication-Efficient Federated Learning in UAV-Enabled Internet of Vehicles
- Asynchronous Federated Learning with Reduced Number of Rounds and with Differential Privacy from Less Aggregated Gaussian Noise
- FedOCR: Communication-Efficient Federated Learning for Scene Text Recognition
- Federated Self-Supervised Learning of Multi-Sensor Representations for Embedded Intelligence
- Dispersed Federated Learning: Vision, Taxonomy, and Future Directions
- How to Put Users in Control of their Data via Federated Pair-Wise Recommendation
- An Isolated Data Island Benchmark Suite for Federated Learning
- Toward Smart Security Enhancement of Federated Learning Networks
- A Federated Multi-View Deep Learning Framework for Privacy-Preserving Recommendations
- Benchmarking Semi-supervised Federated Learning
- GraphFederator: Federated Visual Analysis for Multi-party Graphs
- ESMFL: Efficient and Secure Models for Federated Learning
- A Principled Approach to Data Valuation for Federated Learning
- A Vertical Federated Learning Method for Interpretable Scorecard and Its Application in Credit Scoring
- Fed+: A Family of Fusion Algorithms for Federated Learning
- Effective Federated Adaptive Gradient Methods with Non-IID Decentralized Data
- FLAME: Differentially Private Federated Learning in the Shuffle Model
- Byzantine-Robust Variance-Reduced Federated Learning over Distributed Non-i.i.d. Data
- Dynamic Fusion based Federated Learning for COVID-19 Detection
- When Deep Reinforcement Learning Meets Federated Learning: Intelligent Multi-Timescale Resource Management for Multi-access Edge Computing in 5G Ultra Dense Network
- Pocket Diagnosis: Secure Federated Learning against Poisoning Attack in the Cloud
- Secure Aggregation with Heterogeneous Quantization in Federated Learning
- NIPS
- A Federated Learning Approach to Anomaly Detection in Smart Buildings
- Federated Deep Unfolding for Sparse Recovery
- Containing Future Epidemics with Trustworthy Federated Systems for Ubiquitous Warning and Response
- Semi-supervised Federated Learning for Activity Recognition
- FedSL: Federated Split Learning on Distributed Sequential Data in Recurrent Neural Networks
- Privacy Preservation in Federated Learning: Insights from the GDPR Perspective
- Optimized Power Control for Over-the-Air Federated Edge Learning
- A Novel Privacy-Preserved Recommender System Framework based on Federated Learning
- An Exploratory Analysis on Users' Contributions in Federated Learning
- ??
- Improved Convergence Rates for Non-Convex Federated Learning with Compression
- Accurate and Fast Federated Learning via IID and Communication-Aware Grouping
- Analysis and Optimal Edge Assignment For Hierarchical Federated Learning on Non-IID Data
- Toward Understanding the Influence of Individual Clients in Federated Learning
- Federated Unlearning
- Bayesian Federated Learning over Wireless Networks
- Federated Learning for Internet of Things: Recent Advances, Taxonomy, and Open Challenges
- FedADC: Accelerated Federated Learning with Drift Control
- End-to-End Evaluation of Federated Learning and Split Learning for Internet of Things
- Second-Order Guarantees in Centralized, Federated and Decentralized Nonconvex Optimization
- Prioritized Multi-Criteria Federated Learning
- Multi-Stage Hybrid Federated Learning over Large-Scale Wireless Fog Networks
- Deep Anomaly Detection for Time-series Data in Industrial IoT: A Communication-Efficient On-device Federated Learning Approach
- FPGA-Based Hardware Accelerator of Homomorphic Encryption for Efficient Federated Learning
- Federated Learning in the Sky: Aerial-Ground Air Quality Sensing Framework with UAV Swarms
- Fast-Convergent Federated Learning
- VFL: A Verifiable Federated Learning with Privacy-Preserving for Big Data in Industrial IoT
- FedCTR: Federated Native Ad CTR Prediction with Multi-Platform User Behavior Data
- SAFER: Sparse Secure Aggregation for Federated Learning
- Scalable and Communication-efficient Decentralized Federated Edge Learning with Multi-blockchain Framework
- WAFFLe: Weight Anonymized Factorization for Federated Learning
- Federated Doubly Stochastic Kernel Learning for Vertically Partitioned Data
- Towards Class Imbalance in Federated Learning
- A VCG-based Fair Incentive Mechanism for Federated Learning
- Shuffled Model of Federated Learning: Privacy, Communication and Accuracy Trade-offs
- WAFFLE: Watermarking in Federated Learning
- Accelerating Federated Learning in Heterogeneous Data and Computational Environments
- MICCAIW
- Federated Learning for Breast Density Classification: A Real-World Implementation
- FedDistill: Making Bayesian Model Ensemble Applicable to Federated Learning
- A Real-time Contribution Measurement Method for Participants in Federated Learning
- Blockchain-based Federated Learning for Failure Detection in Industrial IoT
- Estimation of Individual Device Contributions for Incentivizing Federated Learning
- An Incentive Mechanism for Federated Learning in Wireless Cellular network: An Auction Approach
- Experiments of Federated Learning for COVID-19 Chest X-ray Images
- HeteroFL: Computation and Communication Efficient Federated Learning for Heterogeneous Clients
- Fairness-aware Agnostic Federated Learning
- Federated Learning via Posterior Averaging: A New Perspective and Practical Algorithms
- FedAT: A Communication-Efficient Federated Learning Method with Asynchronous Tiers under Non-IID Data
- Oort: Informed Participant Selection for Scalable Federated Learning
- BlockFLA: Accountable Federated Learning via Hybrid Blockchain Architecture
- Local Averaging Helps: Hierarchical Federated Learning and Convergence Analysis
- Adaptive Federated Learning and Digital Twin for Industrial Internet of Things
- Federated Knowledge Distillation
- FLaaS: Federated Learning as a Service
- Low-latency Federated Learning and Blockchain for Edge Association in Digital Twin empowered 6G Networks
- LINDT: Tackling Negative Federated Learning with Local Adaptation
- Toward Multiple Federated Learning Services Resource Sharing in Mobile Edge Networks
- Privacy-Preserving Federated Learning for UAV-Enabled Networks: Learning-Based Joint Scheduling and Resource Management
- Federated Learning with Diversified Preference for Humor Recognition
- Robust Federated Learning with Noisy Labels
- A Systematic Literature Review on Federated Learning: From A Model Quality Perspective
- Vehicular Cooperative Perception Through Action Branching and Federated Reinforcement Learning
- Design and Analysis of Uplink and Downlink Communications for Federated Learning
- Federated Multi-Task Learning for Competing Constraints
- Provable Defense against Privacy Leakage in Federated Learning from Representation Perspective
- Towards Communication-efficient and Attack-Resistant Federated Edge Learning for Industrial Internet of Things
- Federated Learning in Unreliable and Resource-Constrained Cellular Wireless Networks
- Privacy and Robustness in Federated Learning: Attacks and Defenses
- Communication-Efficient Federated Learning with Compensated Overlap-FedAvg
- To Talk or to Work: Energy Efficient Federated Learning over Mobile Devices via the Weight Quantization and 5G Transmission Co-Design
- Cost-Effective Federated Learning Design
- Personalized Federated Learning with First Order Model Optimization
- Turn Signal Prediction: A Federated Learning Case Study
- Decentralized Federated Learning via Mutual Knowledge Transfer
- Federated Block Coordinate Descent Scheme for Learning Global and Personalized Models
- Straggler-Resilient Federated Learning: Leveraging the Interplay Between Statistical Accuracy and System Heterogeneity
- Distillation-Based Semi-Supervised Federated Learning for Communication-Efficient Collaborative Training with Non-IID Private Data
- POSEIDON: Privacy-Preserving Federated Neural Network Learning
- Federated Learning for Computational Pathology on Gigapixel Whole Slide Images
- FedPerf: A Practitioners’ Guide to Performance of Federated Learning Algorithms
-
2019
- Federated Learning for Time Series Forecasting Using LSTM Networks: Exploiting Similarities Through Clustering
- Federated learning-based computation offloading optimization in edge computing-supported internet of things - 69201.
- FFD: A Federated Learning Based Method for Credit Card Fraud Detection - 32.
- Towards faster and better federated learning: A feature fusion approach - 179.
- Collaborative learning on the edges: A case study on connected vehicles
- Federated Learning for Time Series Forecasting Using Hybrid Model
- Peer-to-peer Federated Learning on Graphs
- Complexity of the quorum intersection property of the Federated Byzantine Agreement System
- Federated Heavy Hitters Discovery with Differential Privacy
- Fast Uplink Grant for NOMA: a Federated Learning based Approach
- A Federated Filtering Framework for Internet of Medical Things
- ElfStore: A Resilient Data Storage Service for Federated Edge and Fog Resources
- A Federated Authorization Framework for Distributed Personal Data and Digital Identity
- TickTalk -- Timing API for Dynamically Federated Cyber-Physical Systems
- VM Image Repository and Distribution Models for Federated Clouds: State of the Art, Possible Directions and Open Issues
- Smart Contract Federated Identity Management without Third Party Authentication Services
- A Federated Lightweight Authentication Protocol for the Internet of Things
- Federated PCA with Adaptive Rank Estimation
- Securing HPC using Federated Authentication
- ICLR
- ExpertMatcher: Automating ML Model Selection for Users in Resource Constrained Countries
- Stochastic Channel-Based Federated Learning for Medical Data Privacy Preserving
- A Crowdsourcing Framework for On-Device Federated Learning
- Quality of Service (QoS) Modelling in Federated Cloud Computing
- A science gateway for Exploring the X-ray Transient and variable sky using EGI Federated Cloud
- Mathematical Analysis and Algorithms for Federated Byzantine Agreement Systems
- Proof of Federated Learning: A Novel Energy-recycling Consensus Algorithm
- Federated Imitation Learning: A Novel Framework for Cloud Robotic Systems with Heterogeneous Sensor Data
- Federated Variance-Reduced Stochastic Gradient Descent with Robustness to Byzantine Attacks
- Federated learning-based computation offloading optimization in edge computing-supported internet of things - 69201.
- FFD: A Federated Learning Based Method for Credit Card Fraud Detection - 32.
- FFD: A Federated Learning Based Method for Credit Card Fraud Detection - 32.
- Proof of Federated Learning: A Novel Energy-recycling Consensus Algorithm
- FFD: A Federated Learning Based Method for Credit Card Fraud Detection - 32.
- FFD: A Federated Learning Based Method for Credit Card Fraud Detection - 32.
- FFD: A Federated Learning Based Method for Credit Card Fraud Detection - 32.
- FFD: A Federated Learning Based Method for Credit Card Fraud Detection - 32.
- FFD: A Federated Learning Based Method for Credit Card Fraud Detection - 32.
- VM Image Repository and Distribution Models for Federated Clouds: State of the Art, Possible Directions and Open Issues
- FFD: A Federated Learning Based Method for Credit Card Fraud Detection - 32.
- FFD: A Federated Learning Based Method for Credit Card Fraud Detection - 32.
- Peer-to-peer Federated Learning on Graphs
- Complexity of the quorum intersection property of the Federated Byzantine Agreement System
- Fast Uplink Grant for NOMA: a Federated Learning based Approach
- Smart Contract Federated Identity Management without Third Party Authentication Services
- A Federated Lightweight Authentication Protocol for the Internet of Things
- Securing HPC using Federated Authentication
- ICLR
- ExpertMatcher: Automating ML Model Selection for Users in Resource Constrained Countries
- A Crowdsourcing Framework for On-Device Federated Learning
- A science gateway for Exploring the X-ray Transient and variable sky using EGI Federated Cloud
- Mathematical Analysis and Algorithms for Federated Byzantine Agreement Systems
- Federated Variance-Reduced Stochastic Gradient Descent with Robustness to Byzantine Attacks
- A Federated Filtering Framework for Internet of Medical Things
- ElfStore: A Resilient Data Storage Service for Federated Edge and Fog Resources
- FFD: A Federated Learning Based Method for Credit Card Fraud Detection - 32.
- FFD: A Federated Learning Based Method for Credit Card Fraud Detection - 32.
- FFD: A Federated Learning Based Method for Credit Card Fraud Detection - 32.
- Towards faster and better federated learning: A feature fusion approach - 179.
- FFD: A Federated Learning Based Method for Credit Card Fraud Detection - 32.
- FFD: A Federated Learning Based Method for Credit Card Fraud Detection - 32.
- FFD: A Federated Learning Based Method for Credit Card Fraud Detection - 32.
- FFD: A Federated Learning Based Method for Credit Card Fraud Detection - 32.
- FFD: A Federated Learning Based Method for Credit Card Fraud Detection - 32.
- Stochastic Channel-Based Federated Learning for Medical Data Privacy Preserving
- FFD: A Federated Learning Based Method for Credit Card Fraud Detection - 32.
- FFD: A Federated Learning Based Method for Credit Card Fraud Detection - 32.
- Federated Heavy Hitters Discovery with Differential Privacy
- A Federated Authorization Framework for Distributed Personal Data and Digital Identity
- TickTalk -- Timing API for Dynamically Federated Cyber-Physical Systems
- Federated PCA with Adaptive Rank Estimation
- Quality of Service (QoS) Modelling in Federated Cloud Computing
- Federated Imitation Learning: A Novel Framework for Cloud Robotic Systems with Heterogeneous Sensor Data
- FFD: A Federated Learning Based Method for Credit Card Fraud Detection - 32.
- Smart Contract Federated Identity Management without Third Party Authentication Services
- FFD: A Federated Learning Based Method for Credit Card Fraud Detection - 32.
- FFD: A Federated Learning Based Method for Credit Card Fraud Detection - 32.
- FFD: A Federated Learning Based Method for Credit Card Fraud Detection - 32.
- FFD: A Federated Learning Based Method for Credit Card Fraud Detection - 32.
- FFD: A Federated Learning Based Method for Credit Card Fraud Detection - 32.
- FFD: A Federated Learning Based Method for Credit Card Fraud Detection - 32.
- FFD: A Federated Learning Based Method for Credit Card Fraud Detection - 32.
- FFD: A Federated Learning Based Method for Credit Card Fraud Detection - 32.
- FFD: A Federated Learning Based Method for Credit Card Fraud Detection - 32.
- FFD: A Federated Learning Based Method for Credit Card Fraud Detection - 32.
- FFD: A Federated Learning Based Method for Credit Card Fraud Detection - 32.
- FFD: A Federated Learning Based Method for Credit Card Fraud Detection - 32.
- FFD: A Federated Learning Based Method for Credit Card Fraud Detection - 32.
- FFD: A Federated Learning Based Method for Credit Card Fraud Detection - 32.
-
2002
-
2003
- k-means - 215.
-
2004
- Naive Bayes - 526.
-
2016
- Deep Learning with Differential Privacy
- Membership inference attacks against machine learning models - 18.<br>[code:[csong27/membership-inference](https://github.com/csong27/membership-inference)]
- Membership inference attacks against machine learning models - 18.<br>[code:[csong27/membership-inference](https://github.com/csong27/membership-inference)]
-
2017
- Privacy-preserving deep learning via additively homomorphic encryption - 1345.
- SGX - 497.
- A system for scalable privacy-preserving machine learning - 38.
- SGX
- KDD
- Semi-Federated Scheduling of Parallel Real-Time Tasks on Multiprocessors
- The Odyssey Approach for Optimizing Federated SPARQL Queries
- A Unique One-Time Password Table Sequence Pattern Authentication: Application to Bicol University Union of Federated Faculty Association, Inc. (BUUFFAI) eVoting System
- Institutionally Distributed Deep Learning Networks
- Reservation-Based Federated Scheduling for Parallel Real-Time Tasks
- Federated Control with Hierarchical Multi-Agent Deep Reinforcement Learning
- SGX
- KDD
- The Odyssey Approach for Optimizing Federated SPARQL Queries
- A Unique One-Time Password Table Sequence Pattern Authentication: Application to Bicol University Union of Federated Faculty Association, Inc. (BUUFFAI) eVoting System
- Institutionally Distributed Deep Learning Networks
- Reservation-Based Federated Scheduling for Parallel Real-Time Tasks
- Federated Control with Hierarchical Multi-Agent Deep Reinforcement Learning
- SGX - 497.
- A Unique One-Time Password Table Sequence Pattern Authentication: Application to Bicol University Union of Federated Faculty Association, Inc. (BUUFFAI) eVoting System
- Semi-Federated Scheduling of Parallel Real-Time Tasks on Multiprocessors
-
2018
- Federated learning based proactive content caching in edge computing - 6.
- When edge meets learning: Adaptive control for resource-constrained distributed machine learning - IEEE Conference on Computer Communications. IEEE, 2018: 63-71.
- Federated Kernelized Multi-Task Learning
- {GAZELLE}: A low latency framework for secure neural network inference - 1669.
- ICLR
- Improving Privacy and Trust in Federated Identity Using SAML with Hash Based Encryption Algorithm
- Fair non-monetary scheduling in federated clouds
- A Federated Capability-based Access Control Mechanism for Internet of Things (IoTs)
- Next generation portal for federated testbeds MySlice v2: from prototype to production
- Confederated Modular Differential Equation APIs for Accelerated Algorithm Development and Benchmarking
- umd-verification: Automation of Software Validation for the EGI federated e-Infrastructure
- FedMark: A Marketplace for Federated Data on the Web
- Privacy-Preserving Deep Learning via Weight Transmission.
- Federated AI for building AI Solutions across Multiple Agencies
- C-DLSI: An Extended LSI Tailored for Federated Text Retrieval
- Review of Barriers for Federated Identity Adoption for Users and Organizations
- Heuristics-based Query Reordering for Federated Queries in SPARQL 1.1 and SPARQL-LD
- Federated Byzantine Quorum Systems (Extended Version)
- Recommending Users: Whom to Follow on Federated Social Networks
- Gradient-Leaks: Understanding and Controlling Deanonymization in Federated Learning
- C-DLSI: An Extended LSI Tailored for Federated Text Retrieval
- Review of Barriers for Federated Identity Adoption for Users and Organizations
- Heuristics-based Query Reordering for Federated Queries in SPARQL 1.1 and SPARQL-LD
- Federated Byzantine Quorum Systems (Extended Version)
- Recommending Users: Whom to Follow on Federated Social Networks
- Improving Privacy and Trust in Federated Identity Using SAML with Hash Based Encryption Algorithm
- Fair non-monetary scheduling in federated clouds
- A Federated Capability-based Access Control Mechanism for Internet of Things (IoTs)
- Next generation portal for federated testbeds MySlice v2: from prototype to production
- umd-verification: Automation of Software Validation for the EGI federated e-Infrastructure
- FedMark: A Marketplace for Federated Data on the Web
- Gradient-Leaks: Understanding and Controlling Deanonymization in Federated Learning
- Confederated Modular Differential Equation APIs for Accelerated Algorithm Development and Benchmarking
- Federated AI for building AI Solutions across Multiple Agencies
-
2021
- Federated Nonconvex Sparse Learning
- Fidel: Reconstructing Private Training Samples from Weight Updates in Federated Learning
- Dynamic Federated Learning-Based Economic Framework for Internet-of-Vehicles
- Device Sampling for Heterogeneous Federated Learning: Theory, Algorithms, and Implementation
- Fusion of Federated Learning and Industrial Internet of Things: A Survey
- Federated Learning-Based Risk-Aware Decision toMitigate Fake Task Impacts on CrowdsensingPlatforms
- Federated Learning for 6G: Applications, Challenges, and Opportunities
- IPLS : A Framework for Decentralized Federated Learning
- Federated Learning at the Network Edge: When Not All Nodes are Created Equal
- Federated Learning over Noisy Channels: Convergence Analysis and Design Examples
- FLGUARD: Secure and Private Federated Learning
- Architectural Patterns for the Design of Federated Learning Systems
- Differentially Private Federated Learning for Cancer Prediction
- DiPSeN: Differentially Private Self-normalizing Neural Networks For Adversarial Robustness in Federated Learning
- Robust Blockchained Federated Learning with Model Validation and Proof-of-Stake Inspired Consensus
- Opportunities of Federated Learning in Connected, Cooperative and Automated Industrial Systems
- Bandwidth Allocation for Multiple Federated Learning Services in Wireless Edge Networks
- FedAR: Activity and Resource-Aware Federated Learning Model for Distributed Mobile Robots
- On the Practicality of Differential Privacy in Federated Learning by Tuning Iteration Times
- Personalized Federated Deep Learning for Pain Estimation From Face Images
- Towards Energy Efficient Federated Learning over 5G+ Mobile Devices
- Federated Learning: Opportunities and Challenges
- Auto-weighted Robust Federated Learning with Corrupted Data Sources
- Blockchain Assisted Decentralized Federated Learning (BLADE-FL): Performance Analysis and Resource Allocation
- Federated Learning Based Proactive Handover in Millimeter-wave Vehicular Networks
- Reducing bias and increasing utility by federated generative modeling of medical images using a centralized adversary
- Collaborative Federated Learning For Healthcare: Multi-Modal COVID-19 Diagnosis at the Edge
- FedNS: Improving Federated Learning for collaborative image classification on mobile clients
- Rate Region for Indirect Multiterminal Source Coding in Federated Learning
- Time-Correlated Sparsification for Communication-Efficient Federated Learning
- Vertical federated learning based on DFP and BFGS
- Incentive Mechanism Design for Federated Learning: Hedonic Game Approach
- Federated Intrusion Detection for IoT with Heterogeneous Cohort Privacy
- Transparent Contribution Evaluation for Secure Federated Learning on Blockchain
- Untargeted Poisoning Attack Detection in Federated Learning via Behavior Attestation
- Achieving Linear Speedup with Partial Worker Participation in Non-IID Federated Learning
- FedH2L: Federated Learning with Model and Statistical Heterogeneity
- Dopamine: Differentially Private Federated Learning on Medical Data
- Failure Prediction in Production Line Based on Federated Learning: An Empirical Study
- Covert Model Poisoning Against Federated Learning: Algorithm Design and Optimization
- Self-supervised Cross-silo Federated Neural Architecture Search
- Edge Federated Learning Via Unit-Modulus Over-The-Air Computation (Extended Version)
- Federated Multi-Armed Bandits
- Differential Privacy Meets Federated Learning under Communication Constraints
- FedChain: Secure Proof-of-Stake-based Framework for Federated-blockchain Systems
- Battery-constrained Federated Edge Learning in UAV-enabled IoT for B5G/6G Networks
- Federated Learning over Wireless Device-to-Device Networks: Algorithms and Convergence Analysis
- Gain without Pain: Offsetting DP-injected Nosies Stealthily in Cross-device Federated Learning
- Curse or Redemption? How Data Heterogeneity Affects the Robustness of Federated Learning
- Scaling Federated Learning for Fine-tuning of Large Language Models
- Decentralized Federated Learning Preserves Model and Data Privacy
- Federated Learning in Smart Cities: A Comprehensive Survey
- FEDZIP: A Compression Framework for Communication-Efficient Federated Learning
- FedProf: Optimizing Federated Learning with Dynamic Data Profiling
- Provably Secure Federated Learning against Malicious Clients
- A Bayesian Federated Learning Framework with Multivariate Gaussian Product
- Federated Learning on Non-IID Data Silos: An Experimental Study
- SAFELearning: Enable Backdoor Detectability In Federated Learning With Secure Aggregation
- FedAUX: Leveraging Unlabeled Auxiliary Data in Federated Learning
- Semi-Synchronous Federated Learning
- Learning Rate Optimization for Federated Learning Exploiting Over-the-air Computation
- DEAL: Decremental Energy-Aware Learning in a Federated System
- Estimation of Microphone Clusters in Acoustic Sensor Networks using Unsupervised Federated Learning
- Bias-Variance Reduced Local SGD for Less Heterogeneous Federated Learning
- Federated Learning on the Road: Autonomous Controller Design for Connected and Autonomous Vehicles
- Federated Reconstruction: Partially Local Federated Learning
- Multi-Tier Federated Learning for Vertically Partitioned Data
- Double Momentum SGD for Federated Learning
- Distributed Spectrum and Power Allocation for D2D-U Networks: A Scheme based on NN and Federated Learning
- Federated Acoustic Modeling For Automatic Speech Recognition
- Adaptive Quantization of Model Updates for Communication-Efficient Federated Learning
- Federated Deep AUC Maximization for Heterogeneous Data with a Constant Communication Complexity
- Training Federated GANs with Theoretical Guarantees: A Universal Aggregation Approach
- Federated Learning with Local Differential Privacy: Trade-offs between Privacy, Utility, and Communication
- FedGNN: Federated Graph Neural Network for Privacy-Preserving Recommendation
- FLOP: Federated Learning on Medical Datasets using Partial Networks
- Robust Federated Learning with Attack-Adaptive Aggregation
- Meta Federated Learning
- Privacy-Preserving Self-Taught Federated Learning for Heterogeneous Data
- Stragglers Are Not Disaster: A Hybrid Federated Learning Algorithm with Delayed Gradients
- Efficient Algorithms for Federated Saddle Point Optimization
- The Distributed Discrete Gaussian Mechanism for Federated Learning with Secure Aggregation
- Proximal and Federated Random Reshuffling
- Strong exciton-photon coupling with colloidal quantum dots in a tuneable microcavity
- Enhancing WiFi Multiple Access Performance with Federated Deep Reinforcement Learning
- Achieving Linear Convergence in Federated Learning under Objective and Systems Heterogeneity
- Exploiting Shared Representations for Personalized Federated Learning
- FedU: A Unified Framework for Federated Multi-Task Learning with Laplacian Regularization
- Federated Dropout Learning for Hybrid Beamforming With Spatial Path Index Modulation In Multi-User mmWave-MIMO Systems
- On the Impact of Device and Behavioral Heterogeneity in Federated Learning
- FedBN: Federated Learning on Non-IID Features via Local Batch Normalization
- A first look into the carbon footprint of federated learning
- Federated Learning over Wireless Networks: A Band-limited Coordinated Descent Approach
- A Federated Data-Driven Evolutionary Algorithm
- Scaling Neuroscience Research using Federated Learning
- Federated Evaluation and Tuning for On-Device Personalization: System Design & Applications
- DESED-FL and URBAN-FL: Federated Learning Datasets for Sound Event Detection
- Federated Depression Detection from Multi-SourceMobile Health Data
- Data-Aware Device Scheduling for Federated Edge Learning
- Personalized Federated Learning: A Unified Framework and Universal Optimization Techniques
- When Crowdsensing Meets Federated Learning: Privacy-Preserving Mobile Crowdsensing System
- Making a Case for Federated Learning in the Internet of Vehicles and Intelligent Transportation Systems
- Fast and Sample-Efficient Federated Low Rank Matrix Recovery from Column-wise Linear and Quadratic Projections
- CFLMEC: Cooperative Federated Learning for Mobile Edge Computing
- Privacy-Preserving Wireless Federated Learning Exploiting Inherent Hardware Impairments
- Mobility-Aware Routing and Caching: A Federated Learning Assisted Approach
- CSIT-Free Federated Edge Learning via Reconfigurable Intelligent Surface
- Clustering Algorithm to Detect Adversaries in Federated Learning
- Multiple Kernel-Based Online Federated Learning
- Federated $f$-Differential Privacy
- Sustainable Federated Learning
- Federated Learning for Physical Layer Design
- QuPeL: Quantized Personalization with Applications to Federated Learning
- Estimation of Continuous Blood Pressure from PPG via a Federated Learning Approach
- Wirelessly Powered Federated Edge Learning: Optimal Tradeoffs Between Convergence and Power Transfer
- Distributionally Robust Federated Averaging
- Blockchained Federated Learning for Threat Defense
- Emerging Trends in Federated Learning: From Model Fusion to Federated X Learning
- Federated Multi-armed Bandits with Personalization
- Cybersecurity Threats in Connected and Automated Vehicles based Federated Learning Systems
- Efficient Client Contribution Evaluation for Horizontal Federated Learning
- FjORD: Fair and Accurate Federated Learning under heterogeneous targets with Ordered Dropout
- A Quantitative Metric for Privacy Leakage in Federated Learning
- Federated Edge Learning with Misaligned Over-The-Air Computation
- Scalable federated machine learning with FEDn
- Constrained Differentially Private Federated Learning for Low-bandwidth Devices
- Integrating Over-the-Air Federated Learning and Non-Orthogonal Multiple Access: What Role can RIS Play?
- Federated Learning without Revealing the Decision Boundaries
- Heterogeneity for the Win: One-Shot Federated Clustering
- Privacy-Preserving Distributed SVD via Federated Power
- Towards Personalized Federated Learning
- Secure Bilevel Asynchronous Vertical Federated Learning with Backward Updating
- Blockchain-Based Federated Learning in Mobile Edge Networks with Application in Internet of Vehicles
- Adversarial training in communication constrained federated learning
- Adaptive Transmission Scheduling in Wireless Networks for Asynchronous Federated Learning
- PFA: Privacy-preserving Federated Adaptation for Effective Model Personalization
- A Theorem of the Alternative for Personalized Federated Learning
- Privacy Amplification for Federated Learning via User Sampling and Wireless Aggregation
- Multi-institutional Collaborations for Improving Deep Learning-based Magnetic Resonance Image Reconstruction Using Federated Learning
- Temporal-Structure-Assisted Gradient Aggregation for Over-the-Air Federated Edge Learning
- R-Learning Based Admission Control for Service Federation in Multi-domain 5G Networks
- One for One, or All for All: Equilibria and Optimality of Collaboration in Federated Learning
- Optimization of User Selection and Bandwidth Allocation for Federated Learning in VLC/RF Systems
- Federated Learning with Randomized Douglas-Rachford Splitting Methods
- FedDis: Disentangled Federated Learning for Unsupervised Brain Pathology Segmentation
- Distributed Dynamic Map Fusion via Federated Learning for Intelligent Networked Vehicles
- FedV: Privacy-Preserving Federated Learning over Vertically Partitioned Data
- Personalized Federated Learning using Hypernetworks
- Convergence and Accuracy Trade-Offs in Federated Learning and Meta-Learning
- Blockchains' federation for integrating distributed health data using a patient-centered approach
- FedDG: Federated Domain Generalization on Medical Image Segmentation via Episodic Learning in Continuous Frequency Space
- Deploying Federated Learning in Large-Scale Cellular Networks: Spatial Convergence Analysis
- A Tree-based Federated Learning Approach for Personalized Treatment Effect Estimation from Heterogeneous Data Sources
- Multi-Task Federated Reinforcement Learning with Adversaries
- Federated Functional Gradient Boosting
- Auction Based Clustered Federated Learning in Mobile Edge Computing System
- Private Cross-Silo Federated Learning for Extracting Vaccine Adverse Event Mentions
- Simeon -- Secure Federated Machine Learning Through Iterative Filtering
- Megha: Decentralized Global Fair Scheduling for Federated Clusters
- Sample-based Federated Learning via Mini-batch SSCA
- A Framework for Energy and Carbon Footprint Analysis of Distributed and Federated Edge Learning
- Two Timescale Hybrid Federated Learning with Cooperative D2D Local Model Aggregations
- An Experiment Study on Federated LearningTestbed
- UAV Communications for Sustainable Federated Learning
- Demystifying the Effects of Non-Independence in Federated Learning
- QoS-Constrained Federated Learning Empowered by Intelligent Reflecting Surface
- Server Averaging for Federated Learning
- A Federated Learning Framework in Smart Grid: Securing Power Traces in Collaborative Learning
- Real-time End-to-End Federated Learning: An Automotive Case Study
- Federated Quantum Machine Learning
- The Gradient Convergence Bound of Federated Multi-Agent Reinforcement Learning with Efficient Communication
- Opportunistic Federated Learning: An Exploration of Egocentric Collaboration for Pervasive Computing Applications
- Energy-aware Resource Management for Federated Learning in Multi-access Edge Computing Systems
- FedGP: Correlation-Based Active Client Selection for Heterogeneous Federated Learning
- Hierarchical Quantized Federated Learning: Convergence Analysis and System Design
- Prior-Free Auctions for the Demand Side of Federated Learning
- Privacy and Trust Redefined in Federated Machine Learning
- Federated Learning with Taskonomy for Non-IID Data
- Certifiably-Robust Federated Adversarial Learning via Randomized Smoothing
- 1-Bit Compressive Sensing for Efficient Federated Learning Over the Air
- Model-Contrastive Federated Learning
- User profile-driven large-scale multi-agent learning from demonstration in federated human-robot collaborative environments
- Delay Analysis of Wireless Federated Learning Based on Saddle Point Approximation and Large Deviation Theory
- Federated Learning: A Signal Processing Perspective
- On the Convergence Time of Federated Learning Over Wireless Networks Under Imperfect CSI
- Decentralized and Model-Free Federated Learning: Consensus-Based Distillation in Function Space
- Federated Few-Shot Learning with Adversarial Learning
- PyVertical: A Vertical Federated Learning Framework for Multi-headed SplitNN
- Fast-adapting and Privacy-preserving Federated Recommender System
- An Empirical Evaluation of Cost-based Federated SPARQL Query Processing Engines
- A Federated Learning Framework for Non-Intrusive Load Monitoring
- Federated Learning Meets Blockchain in Edge Computing: Opportunities and Challenges
- FedPandemic: A Cross-Device Federated Learning Approach Towards Elementary Prognosis of Diseases During a Pandemic
- Communication-Efficient Agnostic Federated Averaging
- On-device Federated Learning with Flower
- Empowering Prosumer Communities in Smart Grid with Wireless Communications and Federated Edge Learning
- Joint Optimization of Communications and Federated Learning Over the Air
- Bayesian Variational Federated Learning and Unlearning in Decentralized Networks
- FL-AGCNS: Federated Learning Framework for Automatic Graph Convolutional Network Search
- Threshold-Based Data Exclusion Approach for Energy-Efficient Federated Edge Learning
- Fed-DDM: A Federated Ledgers based Framework for Hierarchical Decentralized Data Marketplaces
- Sample-based and Feature-based Federated Learning via Mini-batch SSCA
- Communication Efficient Federated Learning with Adaptive Quantization
- Towards Causal Federated Learning For Enhanced Robustness and Privacy
- Federated Generalized Face Presentation Attack Detection
- BROADCAST: Reducing Both Stochastic and Compression Noise to Robustify Communication-Efficient Federated Learning
- Privacy-preserving Federated Learning based on Multi-key Homomorphic Encryption
- Resource Rationing for Wireless Federated Learning: Concept, Benefits, and Challenges
- FedGraphNN: A Federated Learning System and Benchmark for Graph Neural Networks
- Federated Learning-based Active Authentication on Mobile Devices
- D-Cliques: Compensating NonIIDness in Decentralized Federated Learning with Topology
- The Role of Cross-Silo Federated Learning in Facilitating Data Sharing in the Agri-Food Sector
- FedSAE: A Novel Self-Adaptive Federated Learning Framework in Heterogeneous Systems
- Decentralized Federated Learning for UAV Networks: Architecture, Challenges, and Opportunities
- Federated Learning for Internet of Things: A Comprehensive Survey
- FedCom: A Byzantine-Robust Local Model Aggregation Rule Using Data Commitment for Federated Learning
- Personalized Semi-Supervised Federated Learning for Human Activity Recognition
- Efficient Ring-topology Decentralized Federated Learning with Deep Generative Models for Industrial Artificial Intelligent
- CSAFL: A Clustered Semi-Asynchronous Federated Learning Framework
- Federated Learning of User Verification Models Without Sharing Embeddings
- FedNLP: A Research Platform for Federated Learning in Natural Language Processing
- Research on Resource Allocation for Efficient Federated Learning
- Federated Learning for Malware Detection in IoT Devices
- An Overview of Federated Learning at the Edge and Distributed Ledger Technologies for Robotic and Autonomous Systems
- Auto-FedAvg: Learnable Federated Averaging for Multi-Institutional Medical Image Segmentation
- Gradient Masked Federated Optimization
- Federated Traffic Synthesizing and Classification Using Generative Adversarial Networks
- A Survey on Federated Learning and its Applications for Accelerating Industrial Internet of Things
- Covert Channel Attack to Federated Learning Systems
- Blockchain based Privacy-Preserved Federated Learning for Medical Images: A Case Study of COVID-19 CT Scans
- Federated Double Deep Q-learning for Joint Delay and Energy Minimization in IoT networks
- Decentralized Federated Averaging
- Robust Federated Learning by Mixture of Experts
- Leveraging Sharing Communities to Achieve Federated Learning for Cybersecurity
- Wireless Federated Learning (WFL) for 6G Networks -- Part II: The Compute-then-Transmit NOMA Paradigm
- FedSup: A Communication-Efficient Federated Learning Fatigue Driving Behaviors Supervision Framework
- Communication-Efficient Federated Learning with Dual-Side Low-Rank Compression
- Communication-Efficient and Personalized Federated Lottery Ticket Learning
- FedDPGAN: Federated Differentially Private Generative Adversarial Networks Framework for the Detection of COVID-19 Pneumonia
- Semi-Decentralized Federated Edge Learning for Fast Convergence on Non-IID Data
- Simultaneous Wireless Information and Power Transfer for Federated Learning
- Multi-resource allocation for federated settings: A non-homogeneous Markov chain model
- Confined Gradient Descent: Privacy-preserving Optimization for Federated Learning
- Towards On-Device Federated Learning: A Direct Acyclic Graph-based Blockchain Approach
- Secure and Efficient Federated Learning Through Layering and Sharding Blockchain
- A Graph Federated Architecture with Privacy Preserving Learning
- Towards Fair Federated Learning with Zero-Shot Data Augmentation
- Pronto: Federated Task Scheduling
- Federated Identity Management (FIdM) Systems Limitation And Solutions
- End-to-End Speech Recognition from Federated Acoustic Models
- From Distributed Machine Learning to Federated Learning: A Survey
- PPFL: Privacy-preserving Federated Learning with Trusted Execution Environments
- Privacy-Preserving Federated Learning on Partitioned Attributes
- Cluster-driven Graph Federated Learning over Multiple Domains
- On In-network learning. A Comparative Study with Federated and Split Learning
- Federated Learning with Fair Averaging
- FedProto: Federated Prototype Learning over Heterogeneous Devices
- GRNN: Generative Regression Neural Network -- A Data Leakage Attack for Federated Learning
- Personalized Federated Learning by Structured and Unstructured Pruning under Data Heterogeneity
- Federated Word2Vec: Leveraging Federated Learning to Encourage Collaborative Representation Learning
- Wireless Federated Learning (WFL) for 6G Networks -- Part I: Research Challenges and Future Trends
- Convergence Analysis and System Design for Federated Learning over Wireless Networks
- Federated Multi-View Learning for Private Medical Data Integration and Analysis
- Density-Aware Federated Imitation Learning for Connected and Automated Vehicles with Unsignalized Intersection
- Federated Face Recognition
- Towards Practical Watermark for Deep Neural Networks in Federated Learning
- FedGL: Federated Graph Learning Framework with Global Self-Supervision
- A Family of Hybrid Federated and Centralized Learning Architectures in Machine Learning
- Loss Tolerant Federated Learning
- The Tags Are Alright: Robust Large-Scale RFID Clone Detection Through Federated Data-Augmented Radio Fingerprinting
- Stronger Privacy for Federated Collaborative Filtering with Implicit Feedback
- Latency Analysis of Consortium Blockchained Federated Learning
- Slashing Communication Traffic in Federated Learning by Transmitting Clustered Model Updates
- Separate but Together: Unsupervised Federated Learning for Speech Enhancement from Non-IID Data
- Federated Unbiased Learning to Rank
- FL-NTK: A Neural Tangent Kernel-based Framework for Federated Learning Convergence Analysis
- An Efficient Learning Framework For Federated XGBoost Using Secret Sharing And Distributed Optimization
- The FeatureCloud AI Store for Federated Learning in Biomedicine and Beyond
- The Federated Tumor Segmentation (FeTS) Challenge
- Clustered Sampling: Low-Variance and Improved Representativity for Clients Selection in Federated Learning
- Federated Learning with Unreliable Clients: Performance Analysis and Mechanism Design
- OpenFL: An open-source framework for Federated Learning
- Node Selection Toward Faster Convergence for Federated Learning on Non-IID Data
- EasyFL: A Low-code Federated Learning Platform For Dummies
- Towards Unsupervised Domain Adaptation for Deep Face Recognition under Privacy Constraints via Federated Learning
- Differentially Private Federated Knowledge Graphs Embedding
- Federated Learning With Highly Imbalanced Audio Data
- DID-eFed: Facilitating Federated Learning as a Service with Decentralized Identities
- Federated Singular Vector Decomposition
- Prototype Guided Federated Learning of Visual Feature Representations
- Private Hierarchical Clustering in Federated Networks
- A Privacy-Preserving Approach to Extraction of Personal Information through Automatic Annotation and Federated Learning
- User Label Leakage from Gradients in Federated Learning
- Separation of Powers in Federated Learning
- Mobile Reconfigurable Intelligent Surfaces for NOMA Networks: Federated Learning Approaches
- Federated Artificial Intelligence for Unified Credit Assessment
- Fed-EINI: An Efficient and Interpretable Inference Framework for Decision Tree Ensembles in Federated Learning
- A Dispersed Federated Learning Framework for 6G-Enabled Autonomous Driving Cars
- Data-Free Knowledge Distillation for Heterogeneous Federated Learning
- Energy Minimized Federated Fog Computing over Passive Optical Networks
- HyFed: A Hybrid Federated Framework for Privacy-preserving Machine Learning
- Byzantine-Resilient Federated Machine Learning via Over-the-Air Computation
- Fast Federated Learning by Balancing Communication Trade-Offs
- Fed-NILM: A Federated Learning-based Non-Intrusive Load Monitoring Method for Privacy-Protection
- Federated Graph Learning -- A Position Paper
- FedScale: Benchmarking Model and System Performance of Federated Learning
- Designing ECG Monitoring Healthcare System with Federated Transfer Learning and Explainable AI
- Networked Federated Multi-Task Learning
- Federated Meta Learning Enhanced Acoustic Radio Cooperative Framework for Ocean of Things Underwater Acoustic Communications
- Concept drift detection and adaptation for federated and continual learning
- Federated Learning for Short-term Residential Energy Demand Forecasting
- A Federated Learning Framework for Nonconvex-PL Minimax Problems
- PPT: A Privacy-Preserving Global Model Training Protocol for Federated Learning in P2P Networks
- FED-$χ^2$: Privacy Preserving Federated Correlation Test
- Federated Learning for Industrial Internet of Things in Future Industries
- Towards a Federated Learning Framework for Heterogeneous Devices of Internet of Things
- On Dynamic Resource Allocation for Blockchain Assisted Federated Learning over Wireless Channels
- Energy-Efficient and Federated Meta-Learning via Projected Stochastic Gradient Ascent
- Unifying Distillation with Personalization in Federated Learning
- Quantum Federated Learning with Quantum Data
- H-FL: A Hierarchical Communication-Efficient and Privacy-Protected Architecture for Federated Learning
- Federated Estimation of Causal Effects from Observational Data
- Dynamic Scheduling for Over-the-Air Federated Edge Learning with Energy Constraints
- Wireless Federated Learning with Limited Communication and Differential Privacy
- Meta-HAR: Federated Representation Learning for Human Activity Recognition
- QLSD: Quantised Langevin stochastic dynamics for Bayesian federated learning
- FedHealth 2: Weighted Federated Transfer Learning via Batch Normalization for Personalized Healthcare
- FedHybrid: A Hybrid Primal-Dual Algorithm Framework for Federated Optimization
- SemiFL: Communication Efficient Semi-Supervised Federated Learning with Unlabeled Clients
- Local Adaptivity in Federated Learning: Convergence and Consistency
- FedCCEA : A Practical Approach of Client Contribution Evaluation for Federated Learning
- SpreadGNN: Serverless Multi-task Federated Learning for Graph Neural Networks
- FedNL: Making Newton-Type Methods Applicable to Federated Learning
- Preservation of the Global Knowledge by Not-True Self Knowledge Distillation in Federated Learning
- Securing Secure Aggregation: Mitigating Multi-Round Privacy Leakage in Federated Learning
- Unsupervised Clustered Federated Learning in Complex Multi-source Acoustic Environments
- Fast Federated Learning in the Presence of Arbitrary Device Unavailability
- Incentive Mechanism for Privacy-Preserving Federated Learning
- Federated Neural Collaborative Filtering
- Federated Hyperparameter Tuning: Challenges, Baselines, and Connections to Weight-Sharing
- No Fear of Heterogeneity: Classifier Calibration for Federated Learning with Non-IID Data
- Cross-Node Federated Graph Neural Network for Spatio-Temporal Data Modeling
- FedDICE: A ransomware spread detection in a distributed integrated clinical environment using federated learning and SDN based mitigation
- Multi-VFL: A Vertical Federated Learning System for Multiple Data and Label Owners
- Vertical Federated Learning without Revealing Intersection Membership
- FedBABU: Towards Enhanced Representation for Federated Image Classification
- Rethinking Architecture Design for Tackling Data Heterogeneity in Federated Learning
- Gradient Disaggregation: Breaking Privacy in Federated Learning by Reconstructing the User Participant Matrix
- Differentially Private Federated Learning via Inexact ADMM
- Exploiting Record Similarity for Practical Vertical Federated Learning
- Federated Learning with Spiking Neural Networks
- Efficient and Less Centralized Federated Learning
- Federated Learning with Buffered Asynchronous Aggregation
- Joint Client Scheduling and Resource Allocation under Channel Uncertainty in Federated Learning
- Federated Learning on Non-IID Data: A Survey
- Adaptive Dynamic Pruning for Non-IID Federated Learning
- Federated Learning Over Wireless Channels: Dynamic Resource Allocation and Task Scheduling
- Understanding the Interplay between Privacy and Robustness in Federated Learning
- DP-NormFedAvg: Normalizing Client Updates for Privacy-Preserving Federated Learning
- CFedAvg: Achieving Efficient Communication and Fast Convergence in Non-IID Federated Learning
- Federated Myopic Community Detection with One-shot Communication
- Decentralized Personalized Federated Min-Max Problems
- Dynamic Gradient Aggregation for Federated Domain Adaptation
- FedNILM: Applying Federated Learning to NILM Applications at the Edge
- On Large-Cohort Training for Federated Learning
- Federated Learning for Internet of Things: A Federated Learning Framework for On-device Anomaly Data Detection
- Over-the-Air Decentralized Federated Learning
- Privacy Assessment of Federated Learning using Private Personalized Layers
- CRFL: Certifiably Robust Federated Learning against Backdoor Attacks
- STAR-RIS Enabled Heterogeneous Networks: Ubiquitous NOMA Communication and Pervasive Federated Learning
- Federated Semi-supervised Medical Image Classification via Inter-client Relation Matching
- Federated Learning over Energy Harvesting Wireless Networks
- FGLP: A Federated Fine-Grained Location Prediction System for Mobile Users
- QuantumFed: A Federated Learning Framework for Collaborative Quantum Training
- Federated CycleGAN for Privacy-Preserving Image-to-Image Translation
- Coded Federated Learning Framework for AI-Based Mobile Application Services with Privacy-Awareness
- Optimized Power Control Design for Over-the-Air Federated Edge Learning
- Quantized Federated Learning under Transmission Delay and Outage Constraints
- Towards Heterogeneous Clients with Elastic Federated Learning
- Federated Learning for Intrusion Detection System: Concepts, Challenges and Future Directions
- Optimality and Stability in Federated Learning: A Game-theoretic Approach
- Locally Differentially Private Federated Learning: Efficient Algorithms with Tight Risk Bounds
- Zero-Shot Federated Learning with New Classes for Audio Classification
- A Vertical Federated Learning Framework for Horizontally Partitioned Labels
- Federated Robustness Propagation: Sharing Adversarial Robustness in Federated Learning
- STEM: A Stochastic Two-Sided Momentum Algorithm Achieving Near-Optimal Sample and Communication Complexities for Federated Learning
- FedXGBoost: Privacy-Preserving XGBoost for Federated Learning
- Is Shapley Value fair? Improving Client Selection for Mavericks in Federated Learning
- FedCM: Federated Learning with Client-level Momentum
- Federated Learning with Positive and Unlabeled Data
- Compositional Federated Learning: Applications in Distributionally Robust Averaging and Meta Learning
- FLRA: A Reference Architecture for Federated Learning Systems
- A Vertical Federated Learning Framework for Graph Convolutional Network
- Enabling Long-Term Cooperation in Cross-Silo Federated Learning: A Repeated Game Perspective
- A Federated Data-Driven Evolutionary Algorithm for Expensive Multi/Many-objective Optimization
- Behavior Mimics Distribution: Combining Individual and Group Behaviors for Federated Learning
- Fine-Grained Data Selection for Improved Energy Efficiency of Federated Edge Learning
- Low-Latency Federated Learning over Wireless Channels with Differential Privacy
- Personalized Federated Learning with Clustered Generalization
- Privacy Threats Analysis to Secure Federated Learning
- Federated Noisy Client Learning
- Federated Graph Classification over Non-IID Graphs
- Subgraph Federated Learning with Missing Neighbor Generation
- Understanding Clipping for Federated Learning: Convergence and Client-Level Differential Privacy
- Implicit Gradient Alignment in Distributed and Federated Learning
- Benchmarking Differential Privacy and Federated Learning for BERT Models
- Multi-task Over-the-Air Federated Learning: A Non-Orthogonal Transmission Approach
- Reward-Based 1-bit Compressed Federated Distillation on Blockchain
- Weight Divergence Driven Divide-and-Conquer Approach for Optimal Federated Learning from non-IID Data
- Federated Dynamic Spectrum Access
- Bottleneck Time Minimization for Distributed Iterative Processes: Speeding Up Gossip-Based Federated Learning on Networked Computers
- Achieving Statistical Optimality of Federated Learning: Beyond Stationary Points
- Federated Learning for Intrusion Detection in IoT Security: A Hybrid Ensemble Approach
- A Comprehensive Survey of Incentive Mechanism for Federated Learning
- Personalized Federated Learning with Gaussian Processes
- UAV-assisted Online Machine Learning over Multi-Tiered Networks: A Hierarchical Nested Personalized Federated Learning Approach
- Faithful Edge Federated Learning: Scalability and Privacy
- Global Knowledge Distillation in Federated Learning
- FedMix: Approximation of Mixup under Mean Augmented Federated Learning
- On Bridging Generic and Personalized Federated Learning
- Segmented Federated Learning for Adaptive Intrusion Detection System
- Gradient-Leakage Resilient Federated Learning
- Byzantine-robust Federated Learning through Spatial-temporal Analysis of Local Model Updates
- Towards Scheduling Federated Deep Learning using Meta-Gradients for Inter-Hospital Learning
- Optimizing the Numbers of Queries and Replies in Federated Learning with Differential Privacy
- Towards Node Liability in Federated Learning: Computational Cost and Network Overhead
- SplitAVG: A heterogeneity-aware federated deep learning method for medical imaging
- Memory-aware curriculum federated learning for breast cancer classification
- Differentially private federated deep learning for multi-site medical image segmentation
- FedFog: Network-Aware Optimization of Federated Learning over Wireless Fog-Cloud Systems
- DER Forecast using Privacy Preserving Federated Learning
- RoFL: Attestable Robustness for Secure Federated Learning
- Management of Resource at the Network Edge for Federated Learning
- Federated Learning with Downlink Device Selection
- Energy Efficient Federated Learning in Integrated Fog-Cloud Computing Enabled Internet-of-Things Networks
- A Payload Optimization Method for Federated Recommender Systems
- Federated Learning as a Mean-Field Game
- Federated Learning for Multi-Center Imaging Diagnostics: A Study in Cardiovascular Disease
- A Federated Semi-Supervised Learning Approach for Network Traffic Classification
- Personalized Federated Learning over non-IID Data for Indoor Localization
- FedAdapt: Adaptive Offloading for IoT Devices in Federated Learning
- Lithography Hotspot Detection via Heterogeneous Federated Learning with Local Adaptation
- Offloading Optimization with Delay Distribution in the 3-tier Federated Cloud, Edge, and Fog Systems
- Personalized Federated Learning via Maximizing Correlation with Sparse and Hierarchical Extensions
- Leveraging a Federation of Knowledge Graphs to Improve Faceted Search in Digital Libraries
- Communication-Efficient Hierarchical Federated Learning for IoT Heterogeneous Systems with Imbalanced Data
- IFedAvg: Interpretable Data-Interoperability for Federated Learning
- Federated Mixture of Experts
- Wigner time delay of a particle elastically scattered by a cluster of zero-range potentials
- Federated Self-Training for Semi-Supervised Audio Recognition
- A Field Guide to Federated Optimization
- DeFed: A Principled Decentralized and Privacy-Preserving Federated Learning Algorithm
- Decentralized and Personalized Federated Learning
- Genetic CFL: Optimization of Hyper-Parameters in Clustered Federated Learning
- Privacy-preserving Spatiotemporal Scenario Generation of Renewable Energies: A Federated Deep Generative Learning Approach
- Federated Whole Prostate Segmentation in MRI with Personalized Neural Architectures
- AutoFL: Enabling Heterogeneity-Aware Energy Efficient Federated Learning
- An Experimental Study of Data Heterogeneity in Federated Learning Methods for Medical Imaging
- RobustFed: A Truth Inference Approach for Robust Federated Learning
- Decentralized federated learning of deep neural networks on non-iid data
- Trends in Blockchain and Federated Learning for Data Sharing in Distributed Platforms
- Federated Learning with Dynamic Transformer for Text to Speech
- RingFed: Reducing Communication Costs in Federated Learning on Non-IID Data
- Relay-Assisted Cooperative Federated Learning
- How Does Cell-Free Massive MIMO Support Multiple Federated Learning Groups?
- Precision-Weighted Federated Learning
- Defending against Reconstruction Attack in Vertical Federated Learning
- Federated Learning using Smart Contracts on Blockchains, based on Reward Driven Approach
- Fed-ensemble: Improving Generalization through Model Ensembling in Federated Learning
- Federated Learning Versus Classical Machine Learning: A Convergence Comparison
- Communication Efficiency in Federated Learning: Achievements and Challenges
- Device Scheduling and Update Aggregation Policies for Asynchronous Federated Learning
- Accelerating Federated Edge Learning via Optimized Probabilistic Device Scheduling
- FedLab: A Flexible Federated Learning Framework
- Federated Learning with Fair Worker Selection: A Multi-Round Submodular Maximization Approach
- Federated Causal Inference in Heterogeneous Observational Data
- Aggregate or Not? Exploring Where to Privatize in DNN Based Federated Learning Under Different Non-IID Scenes
- Preliminary Steps Towards Federated Sentiment Classification
- Decentralized Federated Learning: Balancing Communication and Computing Costs
- Federated Action Recognition on Heterogeneous Embedded Devices
- On The Impact of Client Sampling on Federated Learning Convergence
- LEGATO: A LayerwisE Gradient AggregaTiOn Algorithm for Mitigating Byzantine Attacks in Federated Learning
- Federated Learning Meets Natural Language Processing: A Survey
- New Metrics to Evaluate the Performance and Fairness of Personalized Federated Learning
- Secure Bayesian Federated Analytics for Privacy-Preserving Trend Detection
- HAFLO: GPU-Based Acceleration for Federated Logistic Regression
- QuPeD: Quantized Personalization via Distillation with Applications to Federated Learning
- Sensing and Mapping for Better Roads: Initial Plan for Using Federated Learning and Implementing a Digital Twin to Identify the Road Conditions in a Developing Country -- Sri Lanka
- A Decentralized Federated Learning Framework via Committee Mechanism with Convergence Guarantee
- A Scalable Federated Multi-agent Architecture for Networked Connected Communication Network
- Information Stealing in Federated Learning Systems Based on Generative Adversarial Networks
- Communication-Efficient Federated Learning via Predictive Coding
- Evaluating Federated Learning for Intrusion Detection in Internet of Things: Review and Challenges
- Bit-efficient Numerical Aggregation and Stronger Privacy for Trust in Federated Analytics
- Personalized Federated Learning with Clustering: Non-IID Heart Rate Variability Data Application
- Secure and Privacy-Preserving Federated Learning via Co-Utility
- FedJAX: Federated learning simulation with JAX
- Decentralized Federated Learning with Unreliable Communications
- Multi-task Federated Edge Learning (MtFEEL) in Wireless Networks
- On Addressing Heterogeneity in Federated Learning for Autonomous Vehicles Connected to a Drone Orchestrator
- GIFAIR-FL: An Approach for Group and Individual Fairness in Federated Learning
- User Scheduling for Federated Learning Through Over-the-Air Computation
- Secure Neuroimaging Analysis using Federated Learning with Homomorphic Encryption
- The Effect of Training Parameters and Mechanisms on Decentralized Federated Learning based on MNIST Dataset
- FederatedNILM: A Distributed and Privacy-preserving Framework for Non-intrusive Load Monitoring based on Federated Deep Learning
- A Credibility-aware Swarm-Federated Deep Learning Framework in Internet of Vehicles
- Fed-BEV: A Federated Learning Framework for Modelling Energy Consumption of Battery Electric Vehicles
- ABC-FL: Anomalous and Benign client Classification in Federated Learning
- FedPAGE: A Fast Local Stochastic Gradient Method for Communication-Efficient Federated Learning
- FedMatch: Federated Learning Over Heterogeneous Question Answering Data
- A Contract Theory based Incentive Mechanism for Federated Learning
- Communication Optimization in Large Scale Federated Learning using Autoencoder Compressed Weight Updates
- Dynamic Attention-based Communication-Efficient Federated Learning
- An Operator Splitting View of Federated Learning
- FedPara: Low-rank Hadamard Product Parameterization for Efficient Federated Learning
- Efficient Federated Meta-Learning over Multi-Access Wireless Networks
- Joint Optimization in Edge-Cloud Continuum for Federated Unsupervised Person Re-identification
- Reference Service Model for Federated Identity Management
- Reducing the Communication Cost of Federated Learning through Multistage Optimization
- A Novel Attribute Reconstruction Attack in Federated Learning
- Blockchain-based Trustworthy Federated Learning Architecture
- Aegis: A Trusted, Automatic and Accurate Verification Framework for Vertical Federated Learning
- Fine-tuning is Fine in Federated Learning
- Aggregation Delayed Federated Learning
- Federated Learning with Correlated Data: Taming the Tail for Age-Optimal Industrial IoT
- Wireless Federated Langevin Monte Carlo: Repurposing Channel Noise for Bayesian Sampling and Privacy
- Federated Multi-Target Domain Adaptation
- Fed-TGAN: Federated Learning Framework for Synthesizing Tabular Data
- Learning Federated Representations and Recommendations with Limited Negatives
- Federated Variational Learning for Anomaly Detection in Multivariate Time Series
- Fair and Consistent Federated Learning
- Multi-task Federated Learning for Heterogeneous Pancreas Segmentation
- Towards More Efficient Federated Learning with Better Optimization Objects
- Multi-Center Federated Learning
- Order Optimal One-Shot Federated Learning for non-Convex Loss Functions
- Client Selection Approach in Support of Clustered Federated Learning over Wireless Edge Networks
- Communication-Efficient Federated Learning via Robust Distributed Mean Estimation
- Elastic scattering of slow electrons by carbon nanotubes
- Cross-Silo Federated Learning for Multi-Tier Networks with Vertical and Horizontal Data Partitioning
- Federated Distributionally Robust Optimization for Phase Configuration of RISs
- FedSkel: Efficient Federated Learning on Heterogeneous Systems with Skeleton Gradients Update
- Mobility-Aware Cluster Federated Learning in Hierarchical Wireless Networks
- Accelerating Federated Learning with a Global Biased Optimiser
- SemiFed: Semi-supervised Federated Learning with Consistency and Pseudo-Labeling
- Personalised Federated Learning: A Combinational Approach
- Flexible Clustered Federated Learning for Client-Level Data Distribution Shift
- Anarchic Federated Learning
- Federated Learning Meets Fairness and Differential Privacy
- Back to the Drawing Board: A Critical Evaluation of Poisoning Attacks on Federated Learning
- Federated Multi-Task Learning under a Mixture of Distributions
- Data-Free Evaluation of User Contributions in Federated Learning
- Federated Learning for UAV Swarms Under Class Imbalance and Power Consumption Constraints
- Federated Learning for Open Banking
- Federated Learning for Privacy-Preserving Open Innovation Future on Digital Health
- PIVODL: Privacy-preserving vertical federated learning over distributed labels
- Byzantine Fault-Tolerance in Federated Local SGD under 2f-Redundancy
- Enabling SQL-based Training Data Debugging for Federated Learning
- Federated Reinforcement Learning: Techniques, Applications, and Open Challenges
- Targeting Underrepresented Populations in Precision Medicine: A Federated Transfer Learning Approach
- A Survey and Comparative Study on Multi-Cloud Architectures: Emerging Issues And Challenges For Cloud Federation
- Private Multi-Task Learning: Formulation and Applications to Federated Learning
- FedKD: Communication Efficient Federated Learning via Knowledge Distillation
- Energy-Efficient Massive MIMO for Serving Multiple Federated Learning Groups
- Unit-Modulus Wireless Federated Learning Via Penalty Alternating Minimization
- GRP-FED: Addressing Client Imbalance in Federated Learning via Global-Regularized Personalization
- Federated Reconnaissance: Efficient, Distributed, Class-Incremental Learning
- Asynchronous Federated Learning for Sensor Data with Concept Drift
- Federated Learning: Issues in Medical Application
- FLASHE: Additively Symmetric Homomorphic Encryption for Cross-Silo Federated Learning
- Statistical Estimation and Inference via Local SGD in Federated Learning
- Ground-Assisted Federated Learning in LEO Satellite Constellations
- FedApp: a Research Sandbox for Application Orchestration in Federated Clouds using OpenStack
- GTG-Shapley: Efficient and Accurate Participant Contribution Evaluation in Federated Learning
- Fair Federated Learning for Heterogeneous Face Data
- Reconfigurable Intelligent Surface Empowered Over-the-Air Federated Edge Learning
- On Second-order Optimization Methods for Federated Learning
- Byzantine-Robust Federated Learning via Credibility Assessment on Non-IID Data
- Practical and Secure Federated Recommendation with Personalized Masks
- Generation of Synthetic Electronic Health Records Using a Federated GAN
- Federated Learning Beyond the Star: Local D2D Model Consensus with Global Cluster Sampling
- FedZKT: Zero-Shot Knowledge Transfer towards Heterogeneous On-Device Models in Federated Learning
- Iterated Vector Fields and Conservatism, with Applications to Federated Learning
- System Optimization in Synchronous Federated Training: A Survey
- An Experimental Study of Class Imbalance in Federated Learning
- A distillation-based approach integrating continual learning and federated learning for pervasive services
- Dubhe: Towards Data Unbiasedness with Homomorphic Encryption in Federated Learning Client Selection
- Asynchronous Federated Learning on Heterogeneous Devices: A Survey
- FedCon: A Contrastive Framework for Federated Semi-Supervised Learning
- Multimodal Federated Learning
- Utility Fairness for the Differentially Private Federated Learning
- On the Initial Behavior Monitoring Issues in Federated Learning
- Cost-Effective Federated Learning in Mobile Edge Networks
- Efficient-FedRec: Efficient Federated Learning Framework for Privacy-Preserving News Recommendation
- Federated Ensemble Model-based Reinforcement Learning
- FedTriNet: A Pseudo Labeling Method with Three Players for Federated Semi-supervised Learning
- Critical Learning Periods in Federated Learning
- Source Inference Attacks in Federated Learning
- FedFair: Training Fair Models In Cross-Silo Federated Learning
- AMI-FML: A Privacy-Preserving Federated Machine Learning Framework for AMI
- Exploiting Heterogeneity in Robust Federated Best-Arm Identification
- Federating Scholarly Infrastructures with GraphQL
- SignGuard: Byzantine-robust Federated Learning through Collaborative Malicious Gradient Filtering
- Concept Drift Detection in Federated Networked Systems
- Bayesian AirComp with Sign-Alignment Precoding for Wireless Federated Learning
- A Blockchain based Federated Learning for Message Dissemination in Vehicular Networks
- Fast Federated Edge Learning with Overlapped Communication and Computation and Channel-Aware Fair Client Scheduling
- Hierarchical Electricity and Carbon Trading in Transmission and Distribution Networks Based on Virtual Federated Prosumer
- Federated Learning of Molecular Properties in a Heterogeneous Setting
- Federated Contrastive Learning for Decentralized Unlabeled Medical Images
- Subspace Learning for Personalized Federated Optimization
- Federated Submodel Averaging
- OpenFed: A Comprehensive and Versatile Open-Source Federated Learning Framework
- Personalized Federated Learning for Heterogeneous Clients with Clustered Knowledge Transfer
- Achieving Model Fairness in Vertical Federated Learning
- Comfetch: Federated Learning of Large Networks on Memory-Constrained Clients via Sketching
- Enforcing fairness in private federated learning via the modified method of differential multipliers
- Toward Efficient Federated Learning in Multi-Channeled Mobile Edge Network with Layerd Gradient Compression
- Improving Fairness for Data Valuation in Federated Learning
- Decentralized Wireless Federated Learning with Differential Privacy
- DeSMP: Differential Privacy-exploited Stealthy Model Poisoning Attacks in Federated Learning
- Enabling Large-Scale Federated Learning over Wireless Edge Networks
- Backdoor Attacks on Federated Learning with Lottery Ticket Hypothesis
- In-network Computation for Large-scale Federated Learning over Wireless Edge Networks
- Federated Feature Selection for Cyber-Physical Systems of Systems
- A Generative Federated Learning Framework for Differential Privacy
- Aristotle Cloud Federation: Container Runtimes Technical Report
- FedProc: Prototypical Contrastive Federated Learning on Non-IID data
- AsySQN: Faster Vertical Federated Learning Algorithms with Better Computation Resource Utilization
- MixNN: Protection of Federated Learning Against Inference Attacks by Mixing Neural Network Layers
- Federated Deep Learning with Bayesian Privacy
- FedIPR: Ownership Verification for Federated Deep Neural Network Models
- Federated Learning Algorithms for Generalized Mixed-effects Model (GLMM) on Horizontally Partitioned Data from Distributed Sources
- LightSecAgg: Rethinking Secure Aggregation in Federated Learning
- Federated Learning over Next-Generation Ethernet Passive Optical Networks
- Federated Self-Supervised Contrastive Learning via Ensemble Similarity Distillation
- Opportunistic Federation of CubeSat Constellations: a Game-Changing Paradigm Enabling Enhanced IoT Services in the Sky
- Federated Learning in ASR: Not as Easy as You Think
- Coding for Straggler Mitigation in Federated Learning
- Federated Dropout -- A Simple Approach for Enabling Federated Learning on Resource Constrained Devices
- Lightweight Transformer in Federated Setting for Human Activity Recognition
- Personalized Retrogress-Resilient Framework for Real-World Medical Federated Learning
- FairFed: Enabling Group Fairness in Federated Learning
- SecFL: Confidential Federated Learning using TEEs
- TinyFedTL: Federated Transfer Learning on Tiny Devices
- MedPerf: Open Benchmarking Platform for Medical Artificial Intelligence using Federated Evaluation
- Asynchronous Upper Confidence Bound Algorithms for Federated Linear Bandits
- Privacy enabled Financial Text Classification using Differential Privacy and Federated Learning
- Federating for Learning Group Fair Models
- Secure Aggregation for Buffered Asynchronous Federated Learning
- Blockchain-based Federated Learning: A Comprehensive Survey
- Securing Federated Learning: A Covert Communication-based Approach
- Communication-Efficient Federated Learning with Binary Neural Networks
- FedDQ: Communication-Efficient Federated Learning with Descending Quantization
- Federated Distillation of Natural Language Understanding with Confident Sinkhorns
- SSFL: Tackling Label Deficiency in Federated Learning via Personalized Self-Supervision
- Federated Learning via Plurality Vote
- Two-Bit Aggregation for Communication Efficient and Differentially Private Federated Learning
- Automatic Tuning of Federated Learning Hyper-Parameters from System Perspective
- Towards Federated Learning-Enabled Visible Light Communication in 6G Systems
- Efficient and Private Federated Learning with Partially Trainable Networks
- Federated Learning from Small Datasets
- Enabling On-Device Training of Speech Recognition Models with Federated Dropout
- Neural Tangent Kernel Empowered Federated Learning
- Federated Learning for Big Data: A Survey on Opportunities, Applications, and Future Directions
- FSL: Federated Supermask Learning
- The Skellam Mechanism for Differentially Private Federated Learning
- Gradual Federated Learning with Simulated Annealing
- Dual Attention-Based Federated Learning for Wireless Traffic Prediction
- ProgFed: Effective, Communication, and Computation Efficient Federated Learning by Progressive Training
- Partial Variable Training for Efficient On-Device Federated Learning
- Deep Federated Learning for Autonomous Driving
- Privacy-Preserving Phishing Email Detection Based on Federated Learning and LSTM
- Federated Natural Language Generation for Personalized Dialogue System
- Graph-Fraudster: Adversarial Attacks on Graph Neural Network Based Vertical Federated Learning
- Communication-Efficient Online Federated Learning Framework for Nonlinear Regression
- WAFFLE: Weighted Averaging for Personalized Federated Learning
- Federated Learning Over Cellular-Connected UAV Networks with Non-IID Datasets
- Federated Learning for COVID-19 Detection with Generative Adversarial Networks in Edge Cloud Computing
- FedSpeech: Federated Text-to-Speech with Continual Learning
- Resource-constrained Federated Edge Learning with Heterogeneous Data: Formulation and Analysis
- Federated learning and next generation wireless communications: A survey on bidirectional relationship
- Distribution-Free Federated Learning with Conformal Predictions
- FedSEAL: Semi-Supervised Federated Learning with Self-Ensemble Learning and Negative Learning
- FedMe: Federated Learning via Model Exchange
- Federated Route Leak Detection in Inter-domain Routing with Privacy Guarantee
- Evaluation of Hyperparameter-Optimization Approaches in an Industrial Federated Learning System
- Nothing Wasted: Full Contribution Enforcement in Federated Edge Learning
- FedSLD: Federated Learning with Shared Label Distribution for Medical Image Classification
- Adapt to Adaptation: Learning Personalization for Cross-Silo Federated Learning
- FedMM: Saddle Point Optimization for Federated Adversarial Domain Adaptation
- Blockchain and Federated Edge Learning for Privacy-Preserving Mobile Crowdsensing
- Sim-to-Real Transfer in Multi-agent Reinforcement Networking for Federated Edge Computing
- Semi-asynchronous Hierarchical Federated Learning for Cooperative Intelligent Transportation Systems
- Towards General Deep Leakage in Federated Learning
- Towards Federated Bayesian Network Structure Learning with Continuous Optimization
- BEV-SGD: Best Effort Voting SGD for Analog Aggregation Based Federated Learning against Byzantine Attackers
- Tackling Dynamics in Federated Incremental Learning with Variational Embedding Rehearsal
- User-Centric Federated Learning
- FedHe: Heterogeneous Models and Communication-Efficient Federated Learning
- TsmoBN: Interventional Generalization for Unseen Clients in Federated Learning
- TESSERACT: Gradient Flip Score to Secure Federated Learning Against Model Poisoning Attacks
- A Federated Learning Aggregation Algorithm for Pervasive Computing: Evaluation and Comparison
- Layer-wise Adaptive Model Aggregation for Scalable Federated Learning
- PipAttack: Poisoning Federated Recommender Systems forManipulating Item Promotion
- SecureBoost+ : A High Performance Gradient Boosting Tree Framework for Large Scale Vertical Federated Learning
- Bristle: Decentralized Federated Learning in Byzantine, Non-i.i.d. Environments
- FedGEMS: Federated Learning of Larger Server Models via Selective Knowledge Fusion
- Guess what? You can boost Federated Learning for free
- PRECAD: Privacy-Preserving and Robust Federated Learning via Crypto-Aided Differential Privacy
- DistFL: Distribution-aware Federated Learning for Mobile Scenarios
- WebFed: Cross-platform Federated Learning Framework Based on Web Browser with Local Differential Privacy
- MANDERA: Malicious Node Detection in Federated Learning via Ranking
- Federated Learning over Wireless IoT Networks with Optimized Communication and Resources
- Federated Unlearning via Class-Discriminative Pruning
- Game of Gradients: Mitigating Irrelevant Clients in Federated Learning
- Federated Multiple Label Hashing (FedMLH): Communication Efficient Federated Learning on Extreme Classification Tasks
- Federated Test-Time Adaptive Face Presentation Attack Detection with Dual-Phase Privacy Preservation
- FedParking: A Federated Learning based Parking Space Estimation with Parked Vehicle assisted Edge Computing
- Optimization-Based GenQSGD for Federated Edge Learning
- Robbing the Fed: Directly Obtaining Private Data in Federated Learning with Modified Models
- Semi-Supervised Federated Learning with non-IID Data: Algorithm and System Design
- MarS-FL: A Market Share-based Decision Support Framework for Participation in Federated Learning
- DPCOVID: Privacy-Preserving Federated Covid-19 Detection
- FL-WBC: Enhancing Robustness against Model Poisoning Attacks in Federated Learning from a Client Perspective
- Fault-Tolerant Federated Reinforcement Learning with Theoretical Guarantee
- Differentially Private Federated Bayesian Optimization with Distributed Exploration
- Federated Linear Contextual Bandits
- FedPrune: Towards Inclusive Federated Learning
- What Do We Mean by Generalization in Federated Learning?
- Over-the-Air Aggregation for Federated Learning: Waveform Superposition and Prototype Validation
- Spatio-Temporal Federated Learning for Massive Wireless Edge Networks
- Ensemble Federated Adversarial Training with Non-IID data
- CAFE: Catastrophic Data Leakage in Vertical Federated Learning
- Energy Efficient Resource Allocation in Federated Fog Computing Networks
- Towards Model Agnostic Federated Learning Using Knowledge Distillation
- FeO2: Federated Learning with Opt-Out Differential Privacy
- Communication-Efficient ADMM-based Federated Learning
- DFL: High-Performance Blockchain-Based Federated Learning
- Improving Fairness via Federated Learning
- Federated Semi-Supervised Learning with Class Distribution Mismatch
- Efficient passive membership inference attack in federated learning
- DAdaQuant: Doubly-adaptive quantization for communication-efficient Federated Learning
- Wireless Federated Learning over MIMO Networks: Joint Device Scheduling and Beamforming Design
- To Talk or to Work: Delay Efficient Federated Learning over Mobile Edge Devices
- FedFm: Towards a Robust Federated Learning Approach For Fault Mitigation at the Edge Nodes
- Resource-Efficient Federated Learning
- Robust Federated Learning via Over-The-Air Computation
- Implicit Model Specialization through DAG-based Decentralized Federated Learning
- Federated Split Vision Transformer for COVID-19 CXR Diagnosis using Task-Agnostic Training
- FedGraph: Federated Graph Learning with Intelligent Sampling
- Practical and Light-weight Secure Aggregation for Federated Submodel Learning
- FedFly: Towards Migration in Edge-based Distributed Federated Learning
- Privacy-Preserving Communication-Efficient Federated Multi-Armed Bandits
- Basis Matters: Better Communication-Efficient Second Order Methods for Federated Learning
- A Survey of Fairness-Aware Federated Learning
- Federated Expectation Maximization with heterogeneity mitigation and variance reduction
- Towards Sparse Federated Analytics: Location Heatmaps under Distributed Differential Privacy with Secure Aggregation
- A Personalized Federated Learning Algorithm: an Application in Anomaly Detection
- TEE-based Selective Testing of Local Workers in Federated Learning Systems
- A Cyber Threat Intelligence Sharing Scheme based on Federated Learning for Network Intrusion Detection
- Parameterized Knowledge Transfer for Personalized Federated Learning
- DVFL: A Vertical Federated Learning Method for Dynamic Data
- Federated Learning Attacks Revisited: A Critical Discussion of Gaps, Assumptions, and Evaluation Setups
- FedLess: Secure and Scalable Federated Learning Using Serverless Computing
- Data Selection for Efficient Model Update in Federated Learning
- Sharp Bounds for Federated Averaging (Local SGD) and Continuous Perspective
- Privacy attacks for automatic speech recognition acoustic models in a federated learning framework
- DQRE-SCnet: A novel hybrid approach for selecting users in Federated Learning with Deep-Q-Reinforcement Learning based on Spectral Clustering
- Federated Learning Based on Dynamic Regularization
- AI Federalism: Shaping AI Policy within States in Germany
- Feature Concepts for Data Federative Innovations
- BARFED: Byzantine Attack-Resistant Federated Averaging Based on Outlier Elimination
- Papaya: Practical, Private, and Scalable Federated Learning
- Unified Group Fairness on Federated Learning
- The Internet of Federated Things (IoFT): A Vision for the Future and In-depth Survey of Data-driven Approaches for Federated Learning
- DP-REC: Private & Communication-Efficient Federated Learning
- DACFL: Dynamic Average Consensus Based Federated Learning in Decentralized Topology
- Transmission Power Control for Over-the-Air Federated Averaging at Network Edge
- FedGreen: Federated Learning with Fine-Grained Gradient Compression for Green Mobile Edge Computing
- Fairness, Integrity, and Privacy in a Scalable Blockchain-based Federated Learning System
- STFL: A Temporal-Spatial Federated Learning Framework for Graph Neural Networks
- Flatee: Federated Learning Across Trusted Execution Environments
- Eluding Secure Aggregation in Federated Learning via Model Inconsistency
- Edge-Native Intelligence for 6G Communications Driven by Federated Learning: A Survey of Trends and Challenges
- Attentive Federated Learning for Concept Drift in Distributed 5G Edge Networks
- Federated Learning with Hyperparameter-based Clustering for Electrical Load Forecasting
- Power Allocation for Wireless Federated Learning using Graph Neural Networks
- Federated Learning for Internet of Things: Applications, Challenges, and Opportunities
- On the Tradeoff between Energy, Precision, and Accuracy in Federated Quantized Neural Networks
- FedCG: Leverage Conditional GAN for Protecting Privacy and Maintaining Competitive Performance in Federated Learning
- HADFL: Heterogeneity-aware Decentralized Federated Learning Framework
- Wyner-Ziv Gradient Compression for Federated Learning
- Inference-Time Unlabeled Personalized Federated Learning
- An Energy Consumption Model for Electrical Vehicle Networks via Extended Federated-learning
- FedCostWAvg: A new averaging for better Federated Learning
- Federated Learning for Smart Healthcare: A Survey
- A Vertical Federated Learning Method For Multi-Institutional Credit Scoring: MICS
- Secure Federated Learning for Residential Short Term Load Forecasting
- Differentially Private Federated Learning on Heterogeneous Data
- Personalized Federated Learning through Local Memorization
- EdgeML: Towards Network-Accelerated Federated Learning over Wireless Edge
- FLSys: Toward an Open Ecosystem for Federated Learning Mobile Apps
- A Novel Optimized Asynchronous Federated Learning Framework
- An Expectation-Maximization Perspective on Federated Learning
- Over-the-Air Federated Learning with Retransmissions (Extended Version)
- Detectability of large correlation length inflationary magnetic field with Cherenkov telescopes
- Federated Learning with Domain Generalization
- Broadband Digital Over-the-Air Computation for Asynchronous Federated Edge Learning
- Satellite Based Computing Networks with Federated Learning
- Secure Linear Aggregation Using Decentralized Threshold Additive Homomorphic Encryption For Federated Learning
- Federated Social Recommendation with Graph Neural Network
- Privacy-preserving Federated Adversarial Domain Adaption over Feature Groups for Interpretability
- FedCV: A Federated Learning Framework for Diverse Computer Vision Tasks
- Client Selection in Federated Learning based on Gradients Importance
- High-Performance Ptychographic Reconstruction with Federated Facilities
- ProxyFL: Decentralized Federated Learning through Proxy Model Sharing
- FLIX: A Simple and Communication-Efficient Alternative to Local Methods in Federated Learning
- Incentive Mechanisms for Federated Learning: From Economic and Game Theoretic Perspective
- Forget-SVGD: Particle-Based Bayesian Federated Unlearning
- Jointly Learning from Decentralized (Federated) and Centralized Data to Mitigate Distribution Shift
- Hierarchical Federated Learning based Anomaly Detection using Digital Twins for Smart Healthcare
- Federated Dynamic Neural Network for Deep MIMO Detection
- Efficient Secure Aggregation Based on SHPRG For Federated Learning
- On-Board Federated Learning for Dense LEO Constellations
- Federated Data Science to Break Down Silos [Vision
- FedDropoutAvg: Generalizable federated learning for histopathology image classification
- Non-IID data and Continual Learning processes in Federated Learning: A long road ahead
- An Optimization Framework for Federated Edge Learning
- Federated Deep Learning in Electricity Forecasting: An MCDM Approach
- Resource-Aware Asynchronous Online Federated Learning for Nonlinear Regression
- Federated Gaussian Process: Convergence, Automatic Personalization and Multi-fidelity Modeling
- Local Learning Matters: Rethinking Data Heterogeneity in Federated Learning
- Fed2: Feature-Aligned Federated Learning
- SPATL: Salient Parameter Aggregation and Transfer Learning for Heterogeneous Clients in Federated Learning
- Efficient Federated Learning for AIoT Applications Using Knowledge Distillation
- Robust Federated Learning for execution time-based device model identification under label-flipping attack
- FedHM: Efficient Federated Learning for Heterogeneous Models via Low-rank Factorization
- Anomaly Localization in Model Gradients Under Backdoor Attacks Against Federated Learning
- Communication-Efficient Federated Learning via Quantized Compressed Sensing
- Establishing the Price of Privacy in Federated Data Trading
- Evaluating Gradient Inversion Attacks and Defenses in Federated Learning
- Compare Where It Matters: Using Layer-Wise Regularization To Improve Federated Learning on Heterogeneous Data
- Federated Learning with Adaptive Batchnorm for Personalized Healthcare
- Models of fairness in federated learning
- Context-Aware Online Client Selection for Hierarchical Federated Learning
- Personalized Federated Learning of Driver Prediction Models for Autonomous Driving
- How global observation works in Federated Learning: Integrating vertical training into Horizontal Federated Learning
- The Impact of Data Distribution on Fairness and Robustness in Federated Learning
- FedRAD: Federated Robust Adaptive Distillation
- Joint Superposition Coding and Training for Federated Learning over Multi-Width Neural Networks
- Intrinisic Gradient Compression for Federated Learning
- When the Curious Abandon Honesty: Federated Learning Is Not Private
- Communication and Energy Efficient Slimmable Federated Learning via Superposition Coding and Successive Decoding
- Location Leakage in Federated Signal Maps
- Federated Deep Reinforcement Learning for the Distributed Control of NextG Wireless Networks
- Federated Causal Discovery
- Efficient Batch Homomorphic Encryption for Vertically Federated XGBoost
- Asynchronous Semi-Decentralized Federated Edge Learning for Heterogeneous Clients
- On Convergence of Federated Averaging Langevin Dynamics
- PMFL: Partial Meta-Federated Learning for heterogeneous tasks and its applications on real-world medical records
- Batch Label Inference and Replacement Attacks in Black-Boxed Vertical Federated Learning
- SoK: On the Security & Privacy in Federated Learning
- Federated Two-stage Learning with Sign-based Voting
- Specificity-Preserving Federated Learning for MR Image Reconstruction
- Federated Reinforcement Learning at the Edge
- Efficient Device Scheduling with Multi-Job Federated Learning
- FedSoft: Soft Clustered Federated Learning with Proximal Local Updating
- Communication-Efficient Federated Learning for Neural Machine Translation
- Improving Performance of Federated Learning based Medical Image Analysis in Non-IID Settings using Image Augmentation
- SparseFed: Mitigating Model Poisoning Attacks in Federated Learning with Sparsification
- Optimal Rate Adaption in Federated Learning with Compressed Communications
- Efficient Differentially Private Secure Aggregation for Federated Learning via Hardness of Learning with Errors
- Federated Nearest Neighbor Classification with a Colony of Fruit-Flies: With Supplement
- Federated Learning for Face Recognition with Gradient Correction
- LoSAC: An Efficient Local Stochastic Average Control Method for Federated Optimization
- Blockchain-enabled Server-less Federated Learning
- Data Placement for Multi-Tenant Data Federation on the Cloud
- Limit on intergalactic magnetic field from ultra-high-energy cosmic ray hotspot in Perseus-Pisces region
- Data Valuation for Vertical Federated Learning: An Information-Theoretic Approach
- FLoRA: Single-shot Hyper-parameter Optimization for Federated Learning
- Federated 3GPP Mobile Edge Computing Systems: A Transparent Proxy for Third Party Authentication with Application Mobility Support
- CodedPaddedFL and CodedSecAgg: Straggler Mitigation and Secure Aggregation in Federated Learning
- Quality monitoring of federated Covid-19 lesion segmentation
- Federated Adaptive Causal Estimation (FACE) of Target Treatment Effects
- From Deterioration to Acceleration: A Calibration Approach to Rehabilitating Step Asynchronism in Federated Optimization
- Federated Learning with Heterogeneous Data: A Superquantile Optimization Approach
- Federated Dynamic Sparse Training: Computing Less, Communicating Less, Yet Learning Better
- Cross-Domain Federated Learning in Medical Imaging
- FedNI: Federated Graph Learning with Network Inpainting for Population-Based Disease Prediction
- Semi-Decentralized Federated Edge Learning with Data and Device Heterogeneity
- Certified Federated Adversarial Training
- HarmoFL: Harmonizing Local and Global Drifts in Federated Learning on Heterogeneous Medical Images
- FedPOIRec: Privacy Preserving Federated POI Recommendation with Social Influence
- Hierarchical Over-the-Air Federated Edge Learning
- Tackling System and Statistical Heterogeneity for Federated Learning with Adaptive Client Sampling
- On-the-fly Resource-Aware Model Aggregation for Federated Learning in Heterogeneous Edge
- Energy-Efficient Massive MIMO for Federated Learning: Transmission Designs and Resource Allocations
- FLoBC: A Decentralized Blockchain-Based Federated Learning Framework
- FedLGA: Towards System-Heterogeneity of Federated Learning via Local Gradient Approximation
- A Practical Data-Free Approach to One-shot Federated Learning with Heterogeneity
- FedFR: Joint Optimization Federated Framework for Generic and Personalized Face Recognition
- EIFFeL: Ensuring Integrity for Federated Learning
- Sparsified Secure Aggregation for Privacy-Preserving Federated Learning
- Faster Rates for Compressed Federated Learning with Client-Variance Reduction
- Towards Federated Learning on Time-Evolving Heterogeneous Data
- Fully Decentralized and Federated Low Rank Compressive Sensing
- Attribute Inference Attack of Speech Emotion Recognition in Federated Learning Settings
- Over-the-Air Computation with DFT-spread OFDM for Federated Edge Learning
- Over-the-Air Multi-Task Federated Learning Over MIMO Interference Channel
- Resource-Efficient and Delay-Aware Federated Learning Design under Edge Heterogeneity
- SPIDER: Searching Personalized Neural Architecture for Federated Learning
- Robust Convergence in Federated Learning through Label-wise Clustering
- Adaptive Client Sampling in Federated Learning via Online Learning with Bandit Feedback
- Federated Learning for Cross-block Oil-water Layer Identification
- Feature-context driven Federated Meta-Learning for Rare Disease Prediction
- Training Time Minimization for Federated Edge Learning with Optimized Gradient Quantization and Bandwidth Allocation
- Challenges and approaches for mitigating byzantine attacks in federated learning
- Efficient and Reliable Overlay Networks for Decentralized Federated Learning
- Provably Secure Federated Learning against Malicious Clients
- A Bayesian Federated Learning Framework with Multivariate Gaussian Product
- Personalized Federated Learning: A Unified Framework and Universal Optimization Techniques
- Wirelessly Powered Federated Edge Learning: Optimal Tradeoffs Between Convergence and Power Transfer
- Blockchained Federated Learning for Threat Defense
- FjORD: Fair and Accurate Federated Learning under heterogeneous targets with Ordered Dropout
- Convergence and Accuracy Trade-Offs in Federated Learning and Meta-Learning
- GRNN: Generative Regression Neural Network -- A Data Leakage Attack for Federated Learning
- Federated Multi-View Learning for Private Medical Data Integration and Analysis
- The FeatureCloud AI Store for Federated Learning in Biomedicine and Beyond
- FedNL: Making Newton-Type Methods Applicable to Federated Learning
- Preservation of the Global Knowledge by Not-True Self Knowledge Distillation in Federated Learning
- Federated Neural Collaborative Filtering
- Federated Learning with Spiking Neural Networks
- Federated CycleGAN for Privacy-Preserving Image-to-Image Translation
- Understanding Clipping for Federated Learning: Convergence and Client-Level Differential Privacy
- IFedAvg: Interpretable Data-Interoperability for Federated Learning
- An Experimental Study of Data Heterogeneity in Federated Learning Methods for Medical Imaging
- Accelerating Federated Edge Learning via Optimized Probabilistic Device Scheduling
- The Effect of Training Parameters and Mechanisms on Decentralized Federated Learning based on MNIST Dataset
- Subspace Learning for Personalized Federated Optimization
- Decentralized Wireless Federated Learning with Differential Privacy
- Robbing the Fed: Directly Obtaining Private Data in Federated Learning with Modified Models
- Differentially Private Federated Bayesian Optimization with Distributed Exploration
- IPLS : A Framework for Decentralized Federated Learning
- Untargeted Poisoning Attack Detection in Federated Learning via Behavior Attestation
- Semi-Synchronous Federated Learning
- Federated Learning on the Road: Autonomous Controller Design for Connected and Autonomous Vehicles
- Double Momentum SGD for Federated Learning
- FLOP: Federated Learning on Medical Datasets using Partial Networks
- The Distributed Discrete Gaussian Mechanism for Federated Learning with Secure Aggregation
- Proximal and Federated Random Reshuffling
- FedBN: Federated Learning on Non-IID Features via Local Batch Normalization
- Fast and Sample-Efficient Federated Low Rank Matrix Recovery from Column-wise Linear and Quadratic Projections
- Fast-adapting and Privacy-preserving Federated Recommender System
- Federated Learning of User Verification Models Without Sharing Embeddings
- Towards Fair Federated Learning with Zero-Shot Data Augmentation
- Cluster-driven Graph Federated Learning over Multiple Domains
- On In-network learning. A Comparative Study with Federated and Split Learning
- A Decentralized Federated Learning Framework via Committee Mechanism with Convergence Guarantee
- Federated Test-Time Adaptive Face Presentation Attack Detection with Dual-Phase Privacy Preservation
- Over-the-Air Aggregation for Federated Learning: Waveform Superposition and Prototype Validation
- Basis Matters: Better Communication-Efficient Second Order Methods for Federated Learning
- DACFL: Dynamic Average Consensus Based Federated Learning in Decentralized Topology
- FedDropoutAvg: Generalizable federated learning for histopathology image classification
- Evaluating Gradient Inversion Attacks and Defenses in Federated Learning
- FedRAD: Federated Robust Adaptive Distillation
- When the Curious Abandon Honesty: Federated Learning Is Not Private
- Location Leakage in Federated Signal Maps
- Blockchain-enabled Server-less Federated Learning
- HarmoFL: Harmonizing Local and Global Drifts in Federated Learning on Heterogeneous Medical Images
- SPIDER: Searching Personalized Neural Architecture for Federated Learning
- Adaptive Client Sampling in Federated Learning via Online Learning with Bandit Feedback
- A Vertical Federated Learning Framework for Horizontally Partitioned Labels
- Aristotle Cloud Federation: Container Runtimes Technical Report
- MedPerf: Open Benchmarking Platform for Medical Artificial Intelligence using Federated Evaluation
- Federated Nonconvex Sparse Learning
- Dynamic Federated Learning-Based Economic Framework for Internet-of-Vehicles
- Device Sampling for Heterogeneous Federated Learning: Theory, Algorithms, and Implementation
- Fusion of Federated Learning and Industrial Internet of Things: A Survey
- Federated Learning-Based Risk-Aware Decision toMitigate Fake Task Impacts on CrowdsensingPlatforms
- Federated Learning for 6G: Applications, Challenges, and Opportunities
- Federated Learning at the Network Edge: When Not All Nodes are Created Equal
- Federated Learning over Noisy Channels: Convergence Analysis and Design Examples
- FLGUARD: Secure and Private Federated Learning
- Differentially Private Federated Learning for Cancer Prediction
- DiPSeN: Differentially Private Self-normalizing Neural Networks For Adversarial Robustness in Federated Learning
- Bandwidth Allocation for Multiple Federated Learning Services in Wireless Edge Networks
- FedAR: Activity and Resource-Aware Federated Learning Model for Distributed Mobile Robots
- On the Practicality of Differential Privacy in Federated Learning by Tuning Iteration Times
- Personalized Federated Deep Learning for Pain Estimation From Face Images
- Towards Energy Efficient Federated Learning over 5G+ Mobile Devices
- Federated Learning: Opportunities and Challenges
- Blockchain Assisted Decentralized Federated Learning (BLADE-FL): Performance Analysis and Resource Allocation
- Reducing bias and increasing utility by federated generative modeling of medical images using a centralized adversary
- FedNS: Improving Federated Learning for collaborative image classification on mobile clients
- Rate Region for Indirect Multiterminal Source Coding in Federated Learning
- Time-Correlated Sparsification for Communication-Efficient Federated Learning
- Towards Sparse Federated Analytics: Location Heatmaps under Distributed Differential Privacy with Secure Aggregation
- A Personalized Federated Learning Algorithm: an Application in Anomaly Detection
- TEE-based Selective Testing of Local Workers in Federated Learning Systems
- A Cyber Threat Intelligence Sharing Scheme based on Federated Learning for Network Intrusion Detection
- Parameterized Knowledge Transfer for Personalized Federated Learning
- Improving Performance of Federated Learning based Medical Image Analysis in Non-IID Settings using Image Augmentation
- Hierarchical Federated Learning based Anomaly Detection using Digital Twins for Smart Healthcare
- DVFL: A Vertical Federated Learning Method for Dynamic Data
- Federated Dynamic Neural Network for Deep MIMO Detection
- Efficient Secure Aggregation Based on SHPRG For Federated Learning
- FedLess: Secure and Scalable Federated Learning Using Serverless Computing
- Federated Learning Attacks Revisited: A Critical Discussion of Gaps, Assumptions, and Evaluation Setups
- Data Selection for Efficient Model Update in Federated Learning
- Sharp Bounds for Federated Averaging (Local SGD) and Continuous Perspective
- Privacy attacks for automatic speech recognition acoustic models in a federated learning framework
- DQRE-SCnet: A novel hybrid approach for selecting users in Federated Learning with Deep-Q-Reinforcement Learning based on Spectral Clustering
- Federated Learning Based on Dynamic Regularization
- AI Federalism: Shaping AI Policy within States in Germany
- Feature Concepts for Data Federative Innovations
- BARFED: Byzantine Attack-Resistant Federated Averaging Based on Outlier Elimination
- Papaya: Practical, Private, and Scalable Federated Learning
- SparseFed: Mitigating Model Poisoning Attacks in Federated Learning with Sparsification
- Optimal Rate Adaption in Federated Learning with Compressed Communications
- Efficient Differentially Private Secure Aggregation for Federated Learning via Hardness of Learning with Errors
- Federated Nearest Neighbor Classification with a Colony of Fruit-Flies: With Supplement
- Federated Learning for Face Recognition with Gradient Correction
- LoSAC: An Efficient Local Stochastic Average Control Method for Federated Optimization
- Data Placement for Multi-Tenant Data Federation on the Cloud
- Resource-Aware Asynchronous Online Federated Learning for Nonlinear Regression
- Federated Gaussian Process: Convergence, Automatic Personalization and Multi-fidelity Modeling
- Local Learning Matters: Rethinking Data Heterogeneity in Federated Learning
- SPATL: Salient Parameter Aggregation and Transfer Learning for Heterogeneous Clients in Federated Learning
- Fed2: Feature-Aligned Federated Learning
- Efficient Federated Learning for AIoT Applications Using Knowledge Distillation
- Limit on intergalactic magnetic field from ultra-high-energy cosmic ray hotspot in Perseus-Pisces region
- Robust Federated Learning for execution time-based device model identification under label-flipping attack
- FedHM: Efficient Federated Learning for Heterogeneous Models via Low-rank Factorization
- Anomaly Localization in Model Gradients Under Backdoor Attacks Against Federated Learning
- Communication-Efficient Federated Learning via Quantized Compressed Sensing
- Establishing the Price of Privacy in Federated Data Trading
- Efficient Batch Homomorphic Encryption for Vertically Federated XGBoost
- Asynchronous Semi-Decentralized Federated Edge Learning for Heterogeneous Clients
- On Convergence of Federated Averaging Langevin Dynamics
- PMFL: Partial Meta-Federated Learning for heterogeneous tasks and its applications on real-world medical records
- Batch Label Inference and Replacement Attacks in Black-Boxed Vertical Federated Learning
- Compare Where It Matters: Using Layer-Wise Regularization To Improve Federated Learning on Heterogeneous Data
- Federated Learning with Adaptive Batchnorm for Personalized Healthcare
- Unified Group Fairness on Federated Learning
- The Internet of Federated Things (IoFT): A Vision for the Future and In-depth Survey of Data-driven Approaches for Federated Learning
- Data Valuation for Vertical Federated Learning: An Information-Theoretic Approach
- FLoRA: Single-shot Hyper-parameter Optimization for Federated Learning
- DP-REC: Private & Communication-Efficient Federated Learning
- Transmission Power Control for Over-the-Air Federated Averaging at Network Edge
- FedGreen: Federated Learning with Fine-Grained Gradient Compression for Green Mobile Edge Computing
- Models of fairness in federated learning
- SoK: On the Security & Privacy in Federated Learning
- Federated Two-stage Learning with Sign-based Voting
- Fairness, Integrity, and Privacy in a Scalable Blockchain-based Federated Learning System
- STFL: A Temporal-Spatial Federated Learning Framework for Graph Neural Networks
- Flatee: Federated Learning Across Trusted Execution Environments
- Eluding Secure Aggregation in Federated Learning via Model Inconsistency
- Edge-Native Intelligence for 6G Communications Driven by Federated Learning: A Survey of Trends and Challenges
- Specificity-Preserving Federated Learning for MR Image Reconstruction
- Attentive Federated Learning for Concept Drift in Distributed 5G Edge Networks
- Federated Learning with Hyperparameter-based Clustering for Electrical Load Forecasting
- Power Allocation for Wireless Federated Learning using Graph Neural Networks
- Federated Reinforcement Learning at the Edge
- Federated Learning for Internet of Things: Applications, Challenges, and Opportunities
- On the Tradeoff between Energy, Precision, and Accuracy in Federated Quantized Neural Networks
- Efficient Device Scheduling with Multi-Job Federated Learning
- Layer-wise Adaptive Model Aggregation for Scalable Federated Learning
- PipAttack: Poisoning Federated Recommender Systems forManipulating Item Promotion
- SecureBoost+ : A High Performance Gradient Boosting Tree Framework for Large Scale Vertical Federated Learning
- Bristle: Decentralized Federated Learning in Byzantine, Non-i.i.d. Environments
- FedGEMS: Federated Learning of Larger Server Models via Selective Knowledge Fusion
- Context-Aware Online Client Selection for Hierarchical Federated Learning
- Guess what? You can boost Federated Learning for free
- PRECAD: Privacy-Preserving and Robust Federated Learning via Crypto-Aided Differential Privacy
- DistFL: Distribution-aware Federated Learning for Mobile Scenarios
- MANDERA: Malicious Node Detection in Federated Learning via Ranking
- Federated Learning over Wireless IoT Networks with Optimized Communication and Resources
- Federated Unlearning via Class-Discriminative Pruning
- Game of Gradients: Mitigating Irrelevant Clients in Federated Learning
- Federated Multiple Label Hashing (FedMLH): Communication Efficient Federated Learning on Extreme Classification Tasks
- Personalized Federated Learning of Driver Prediction Models for Autonomous Driving
- FedSoft: Soft Clustered Federated Learning with Proximal Local Updating
- FedParking: A Federated Learning based Parking Space Estimation with Parked Vehicle assisted Edge Computing
- Optimization-Based GenQSGD for Federated Edge Learning
- Semi-Supervised Federated Learning with non-IID Data: Algorithm and System Design
- MarS-FL: A Market Share-based Decision Support Framework for Participation in Federated Learning
- DPCOVID: Privacy-Preserving Federated Covid-19 Detection
- FL-WBC: Enhancing Robustness against Model Poisoning Attacks in Federated Learning from a Client Perspective
- Fault-Tolerant Federated Reinforcement Learning with Theoretical Guarantee
- Federated Linear Contextual Bandits
- What Do We Mean by Generalization in Federated Learning?
- Spatio-Temporal Federated Learning for Massive Wireless Edge Networks
- Ensemble Federated Adversarial Training with Non-IID data
- On-Board Federated Learning for Dense LEO Constellations
- FedCG: Leverage Conditional GAN for Protecting Privacy and Maintaining Competitive Performance in Federated Learning
- HADFL: Heterogeneity-aware Decentralized Federated Learning Framework
- Wyner-Ziv Gradient Compression for Federated Learning
- Inference-Time Unlabeled Personalized Federated Learning
- An Energy Consumption Model for Electrical Vehicle Networks via Extended Federated-learning
- How global observation works in Federated Learning: Integrating vertical training into Horizontal Federated Learning
- Federated Data Science to Break Down Silos [Vision
- FedCostWAvg: A new averaging for better Federated Learning
- Federated Learning for Smart Healthcare: A Survey
- A Vertical Federated Learning Method For Multi-Institutional Credit Scoring: MICS
- Secure Federated Learning for Residential Short Term Load Forecasting
- Differentially Private Federated Learning on Heterogeneous Data
- Personalized Federated Learning through Local Memorization
- The Impact of Data Distribution on Fairness and Robustness in Federated Learning
- CAFE: Catastrophic Data Leakage in Vertical Federated Learning
- Non-IID data and Continual Learning processes in Federated Learning: A long road ahead
- Energy Efficient Resource Allocation in Federated Fog Computing Networks
- EdgeML: Towards Network-Accelerated Federated Learning over Wireless Edge
- Towards Model Agnostic Federated Learning Using Knowledge Distillation
- FeO2: Federated Learning with Opt-Out Differential Privacy
- Communication-Efficient ADMM-based Federated Learning
- FLSys: Toward an Open Ecosystem for Federated Learning Mobile Apps
- A Novel Optimized Asynchronous Federated Learning Framework
- An Expectation-Maximization Perspective on Federated Learning
- Joint Superposition Coding and Training for Federated Learning over Multi-Width Neural Networks
- DFL: High-Performance Blockchain-Based Federated Learning
- Improving Fairness via Federated Learning
- Federated Semi-Supervised Learning with Class Distribution Mismatch
- Efficient passive membership inference attack in federated learning
- Wireless Federated Learning over MIMO Networks: Joint Device Scheduling and Beamforming Design
- To Talk or to Work: Delay Efficient Federated Learning over Mobile Edge Devices
- Intrinisic Gradient Compression for Federated Learning
- FedFm: Towards a Robust Federated Learning Approach For Fault Mitigation at the Edge Nodes
- Resource-Efficient Federated Learning
- Robust Federated Learning via Over-The-Air Computation
- Communication and Energy Efficient Slimmable Federated Learning via Superposition Coding and Successive Decoding
- Over-the-Air Federated Learning with Retransmissions (Extended Version)
- Detectability of large correlation length inflationary magnetic field with Cherenkov telescopes
- Federated Learning with Domain Generalization
- An Optimization Framework for Federated Edge Learning
- Federated Deep Learning in Electricity Forecasting: An MCDM Approach
- Broadband Digital Over-the-Air Computation for Asynchronous Federated Edge Learning
- Satellite Based Computing Networks with Federated Learning
- Secure Linear Aggregation Using Decentralized Threshold Additive Homomorphic Encryption For Federated Learning
- Federated Social Recommendation with Graph Neural Network
- Federated Deep Reinforcement Learning for the Distributed Control of NextG Wireless Networks
- Privacy-preserving Federated Adversarial Domain Adaption over Feature Groups for Interpretability
- Implicit Model Specialization through DAG-based Decentralized Federated Learning
- FedGraph: Federated Graph Learning with Intelligent Sampling
- Practical and Light-weight Secure Aggregation for Federated Submodel Learning
- FedFly: Towards Migration in Edge-based Distributed Federated Learning
- Privacy-Preserving Communication-Efficient Federated Multi-Armed Bandits
- A Survey of Fairness-Aware Federated Learning
- FedCV: A Federated Learning Framework for Diverse Computer Vision Tasks
- Client Selection in Federated Learning based on Gradients Importance
- High-Performance Ptychographic Reconstruction with Federated Facilities
- ProxyFL: Decentralized Federated Learning through Proxy Model Sharing
- Incentive Mechanisms for Federated Learning: From Economic and Game Theoretic Perspective
- Forget-SVGD: Particle-Based Bayesian Federated Unlearning
- Jointly Learning from Decentralized (Federated) and Centralized Data to Mitigate Distribution Shift
- Communication-Efficient Federated Learning for Neural Machine Translation
- Federated Causal Discovery
- Federated Expectation Maximization with heterogeneity mitigation and variance reduction
- Federated 3GPP Mobile Edge Computing Systems: A Transparent Proxy for Third Party Authentication with Application Mobility Support
- CodedPaddedFL and CodedSecAgg: Straggler Mitigation and Secure Aggregation in Federated Learning
- Quality monitoring of federated Covid-19 lesion segmentation
- Federated Adaptive Causal Estimation (FACE) of Target Treatment Effects
- From Deterioration to Acceleration: A Calibration Approach to Rehabilitating Step Asynchronism in Federated Optimization
- Federated Learning with Heterogeneous Data: A Superquantile Optimization Approach
- Federated Dynamic Sparse Training: Computing Less, Communicating Less, Yet Learning Better
- Cross-Domain Federated Learning in Medical Imaging
- FedNI: Federated Graph Learning with Network Inpainting for Population-Based Disease Prediction
- Semi-Decentralized Federated Edge Learning with Data and Device Heterogeneity
- Certified Federated Adversarial Training
- FedPOIRec: Privacy Preserving Federated POI Recommendation with Social Influence
- Hierarchical Over-the-Air Federated Edge Learning
- Tackling System and Statistical Heterogeneity for Federated Learning with Adaptive Client Sampling
- On-the-fly Resource-Aware Model Aggregation for Federated Learning in Heterogeneous Edge
- Energy-Efficient Massive MIMO for Federated Learning: Transmission Designs and Resource Allocations
- FLoBC: A Decentralized Blockchain-Based Federated Learning Framework
- FedLGA: Towards System-Heterogeneity of Federated Learning via Local Gradient Approximation
- A Practical Data-Free Approach to One-shot Federated Learning with Heterogeneity
- FedFR: Joint Optimization Federated Framework for Generic and Personalized Face Recognition
- EIFFeL: Ensuring Integrity for Federated Learning
- Sparsified Secure Aggregation for Privacy-Preserving Federated Learning
- Faster Rates for Compressed Federated Learning with Client-Variance Reduction
- Towards Federated Learning on Time-Evolving Heterogeneous Data
- Fully Decentralized and Federated Low Rank Compressive Sensing
- Attribute Inference Attack of Speech Emotion Recognition in Federated Learning Settings
- Over-the-Air Computation with DFT-spread OFDM for Federated Edge Learning
- Over-the-Air Multi-Task Federated Learning Over MIMO Interference Channel
- Resource-Efficient and Delay-Aware Federated Learning Design under Edge Heterogeneity
- Robust Convergence in Federated Learning through Label-wise Clustering
- Federated Learning for Cross-block Oil-water Layer Identification
- Feature-context driven Federated Meta-Learning for Rare Disease Prediction
- Training Time Minimization for Federated Edge Learning with Optimized Gradient Quantization and Bandwidth Allocation
- Challenges and approaches for mitigating byzantine attacks in federated learning
- Efficient and Reliable Overlay Networks for Decentralized Federated Learning
- Federated Learning Versus Classical Machine Learning: A Convergence Comparison
- Multi-task Federated Edge Learning (MtFEEL) in Wireless Networks
- Coded Federated Learning Framework for AI-Based Mobile Application Services with Privacy-Awareness
- Dubhe: Towards Data Unbiasedness with Homomorphic Encryption in Federated Learning Client Selection
- Byzantine-Robust Federated Learning via Credibility Assessment on Non-IID Data
- Dubhe: Towards Data Unbiasedness with Homomorphic Encryption in Federated Learning Client Selection
- Critical Learning Periods in Federated Learning
- Enabling Large-Scale Federated Learning over Wireless Edge Networks
- WebFed: Cross-platform Federated Learning Framework Based on Web Browser with Local Differential Privacy
- FedPrune: Towards Inclusive Federated Learning
- DAdaQuant: Doubly-adaptive quantization for communication-efficient Federated Learning
- Federated Split Vision Transformer for COVID-19 CXR Diagnosis using Task-Agnostic Training
- FedGL: Federated Graph Learning Framework with Global Self-Supervision
- The Tags Are Alright: Robust Large-Scale RFID Clone Detection Through Federated Data-Augmented Radio Fingerprinting
- Federated Singular Vector Decomposition
- Prototype Guided Federated Learning of Visual Feature Representations
- User Label Leakage from Gradients in Federated Learning
- A Federated Learning Framework for Nonconvex-PL Minimax Problems
- SpreadGNN: Serverless Multi-task Federated Learning for Graph Neural Networks
- No Fear of Heterogeneity: Classifier Calibration for Federated Learning with Non-IID Data
- Gradient Disaggregation: Breaking Privacy in Federated Learning by Reconstructing the User Participant Matrix
- On Large-Cohort Training for Federated Learning
- A Vertical Federated Learning Framework for Graph Convolutional Network
- Multi-task Over-the-Air Federated Learning: A Non-Orthogonal Transmission Approach
- Optimizing the Numbers of Queries and Replies in Federated Learning with Differential Privacy
- SplitAVG: A heterogeneity-aware federated deep learning method for medical imaging
- Memory-aware curriculum federated learning for breast cancer classification
- FedFog: Network-Aware Optimization of Federated Learning over Wireless Fog-Cloud Systems
- Federated Learning with Local Differential Privacy: Trade-offs between Privacy, Utility, and Communication
- A Survey on Federated Learning and its Applications for Accelerating Industrial Internet of Things
- Federated Mixture of Experts
- DeFed: A Principled Decentralized and Privacy-Preserving Federated Learning Algorithm
- Multi-institutional Collaborations for Improving Deep Learning-based Magnetic Resonance Image Reconstruction Using Federated Learning
- DESED-FL and URBAN-FL: Federated Learning Datasets for Sound Event Detection
- Data-Aware Device Scheduling for Federated Edge Learning
- Privacy-Preserving Wireless Federated Learning Exploiting Inherent Hardware Impairments
- CSIT-Free Federated Edge Learning via Reconfigurable Intelligent Surface
- Federated Learning for Physical Layer Design
- Estimation of Continuous Blood Pressure from PPG via a Federated Learning Approach
- Distributionally Robust Federated Averaging
- Blockchained Federated Learning for Threat Defense
- Emerging Trends in Federated Learning: From Model Fusion to Federated X Learning
- Federated Multi-armed Bandits with Personalization
- Cybersecurity Threats in Connected and Automated Vehicles based Federated Learning Systems
- Efficient Client Contribution Evaluation for Horizontal Federated Learning
- Constrained Differentially Private Federated Learning for Low-bandwidth Devices
- Integrating Over-the-Air Federated Learning and Non-Orthogonal Multiple Access: What Role can RIS Play?
- Blockchain-Based Federated Learning in Mobile Edge Networks with Application in Internet of Vehicles
- PFA: Privacy-preserving Federated Adaptation for Effective Model Personalization
- Deploying Federated Learning in Large-Scale Cellular Networks: Spatial Convergence Analysis
- Auction Based Clustered Federated Learning in Mobile Edge Computing System
- Megha: Decentralized Global Fair Scheduling for Federated Clusters
- Sample-based Federated Learning via Mini-batch SSCA
- Two Timescale Hybrid Federated Learning with Cooperative D2D Local Model Aggregations
- Federated Quantum Machine Learning
- The Gradient Convergence Bound of Federated Multi-Agent Reinforcement Learning with Efficient Communication
- Energy-aware Resource Management for Federated Learning in Multi-access Edge Computing Systems
- Hierarchical Quantized Federated Learning: Convergence Analysis and System Design
- Federated Learning with Taskonomy for Non-IID Data
- User profile-driven large-scale multi-agent learning from demonstration in federated human-robot collaborative environments
- Federated Learning: A Signal Processing Perspective
- A Tree-based Federated Learning Approach for Personalized Treatment Effect Estimation from Heterogeneous Data Sources
- Multi-Task Federated Reinforcement Learning with Adversaries
- Robust Federated Learning by Mixture of Experts
- FedSup: A Communication-Efficient Federated Learning Fatigue Driving Behaviors Supervision Framework
- FedDPGAN: Federated Differentially Private Generative Adversarial Networks Framework for the Detection of COVID-19 Pneumonia
- Federated Learning with Fair Averaging
- OpenFL: An open-source framework for Federated Learning
- Towards Unsupervised Domain Adaptation for Deep Face Recognition under Privacy Constraints via Federated Learning
- DID-eFed: Facilitating Federated Learning as a Service with Decentralized Identities
- Separation of Powers in Federated Learning
- Mobile Reconfigurable Intelligent Surfaces for NOMA Networks: Federated Learning Approaches
- Federated Artificial Intelligence for Unified Credit Assessment
- A Dispersed Federated Learning Framework for 6G-Enabled Autonomous Driving Cars
- Concept drift detection and adaptation for federated and continual learning
- Incentive Mechanism for Privacy-Preserving Federated Learning
- Vertical Federated Learning without Revealing Intersection Membership
- Federated Learning Over Wireless Channels: Dynamic Resource Allocation and Task Scheduling
- Federated Learning with Buffered Asynchronous Aggregation
- Understanding the Interplay between Privacy and Robustness in Federated Learning
- CFedAvg: Achieving Efficient Communication and Fast Convergence in Non-IID Federated Learning
- Federated Myopic Community Detection with One-shot Communication
- Decentralized Personalized Federated Min-Max Problems
- Dynamic Gradient Aggregation for Federated Domain Adaptation
- Privacy Assessment of Federated Learning using Private Personalized Layers
- Locally Differentially Private Federated Learning: Efficient Algorithms with Tight Risk Bounds
- Federated Robustness Propagation: Sharing Adversarial Robustness in Federated Learning
- STEM: A Stochastic Two-Sided Momentum Algorithm Achieving Near-Optimal Sample and Communication Complexities for Federated Learning
- FedXGBoost: Privacy-Preserving XGBoost for Federated Learning
- Federated Noisy Client Learning
- Federated Graph Classification over Non-IID Graphs
- Subgraph Federated Learning with Missing Neighbor Generation
- Is Shapley Value fair? Improving Client Selection for Mavericks in Federated Learning
- FedCM: Federated Learning with Client-level Momentum
- Federated Learning with Positive and Unlabeled Data
- FLRA: A Reference Architecture for Federated Learning Systems
- Enabling Long-Term Cooperation in Cross-Silo Federated Learning: A Repeated Game Perspective
- Behavior Mimics Distribution: Combining Individual and Group Behaviors for Federated Learning
- Fine-Grained Data Selection for Improved Energy Efficiency of Federated Edge Learning
- Personalized Federated Learning with Clustered Generalization
- Privacy Threats Analysis to Secure Federated Learning
- Weight Divergence Driven Divide-and-Conquer Approach for Optimal Federated Learning from non-IID Data
- Bottleneck Time Minimization for Distributed Iterative Processes: Speeding Up Gossip-Based Federated Learning on Networked Computers
- Achieving Statistical Optimality of Federated Learning: Beyond Stationary Points
- Federated Causal Inference in Heterogeneous Observational Data
- Secure and Privacy-Preserving Federated Learning via Co-Utility
- A Credibility-aware Swarm-Federated Deep Learning Framework in Internet of Vehicles
- Efficient Federated Meta-Learning over Multi-Access Wireless Networks
- Reducing the Communication Cost of Federated Learning through Multistage Optimization
- Federated Multi-Target Domain Adaptation
- Multi-task Federated Learning for Heterogeneous Pancreas Segmentation
- Delay Analysis of Wireless Federated Learning Based on Saddle Point Approximation and Large Deviation Theory
- Federated Word2Vec: Leveraging Federated Learning to Encourage Collaborative Representation Learning
- Convergence Analysis and System Design for Federated Learning over Wireless Networks
- Density-Aware Federated Imitation Learning for Connected and Automated Vehicles with Unsignalized Intersection
- Towards Practical Watermark for Deep Neural Networks in Federated Learning
- A Family of Hybrid Federated and Centralized Learning Architectures in Machine Learning
- FLIX: A Simple and Communication-Efficient Alternative to Local Methods in Federated Learning
- Federated Learning for Cross-block Oil-water Layer Identification
- Opportunities of Federated Learning in Connected, Cooperative and Automated Industrial Systems
- Exploiting Shared Representations for Personalized Federated Learning
- Training Federated GANs with Theoretical Guarantees: A Universal Aggregation Approach
- FedGNN: Federated Graph Neural Network for Privacy-Preserving Recommendation
- FedDG: Federated Domain Generalization on Medical Image Segmentation via Episodic Learning in Continuous Frequency Space
- Private Cross-Silo Federated Learning for Extracting Vaccine Adverse Event Mentions
- A Payload Optimization Method for Federated Recommender Systems
- A Quantitative Metric for Privacy Leakage in Federated Learning
- Privacy-Preserving Distributed SVD via Federated Power
- Towards Personalized Federated Learning
- Adaptive Transmission Scheduling in Wireless Networks for Asynchronous Federated Learning
- A Theorem of the Alternative for Personalized Federated Learning
- Temporal-Structure-Assisted Gradient Aggregation for Over-the-Air Federated Edge Learning
- Federated Learning without Revealing the Decision Boundaries
- R-Learning Based Admission Control for Service Federation in Multi-domain 5G Networks
- One for One, or All for All: Equilibria and Optimality of Collaboration in Federated Learning
- Optimization of User Selection and Bandwidth Allocation for Federated Learning in VLC/RF Systems
- Federated Learning with Randomized Douglas-Rachford Splitting Methods
- Personalized Federated Learning using Hypernetworks
- Blockchains' federation for integrating distributed health data using a patient-centered approach
- A Framework for Energy and Carbon Footprint Analysis of Distributed and Federated Edge Learning
- UAV Communications for Sustainable Federated Learning
- Demystifying the Effects of Non-Independence in Federated Learning
- QoS-Constrained Federated Learning Empowered by Intelligent Reflecting Surface
- Server Averaging for Federated Learning
- A Federated Learning Framework in Smart Grid: Securing Power Traces in Collaborative Learning
- Real-time End-to-End Federated Learning: An Automotive Case Study
- 1-Bit Compressive Sensing for Efficient Federated Learning Over the Air
- Federated Few-Shot Learning with Adversarial Learning
- PyVertical: A Vertical Federated Learning Framework for Multi-headed SplitNN
- An Empirical Evaluation of Cost-based Federated SPARQL Query Processing Engines
- FedPara: Low-rank Hadamard Product Parameterization for Efficient Federated Learning
- Joint Optimization in Edge-Cloud Continuum for Federated Unsupervised Person Re-identification
- Reference Service Model for Federated Identity Management
- A Novel Attribute Reconstruction Attack in Federated Learning
- Blockchain-based Trustworthy Federated Learning Architecture
- Aegis: A Trusted, Automatic and Accurate Verification Framework for Vertical Federated Learning
- Fine-tuning is Fine in Federated Learning
- Aggregation Delayed Federated Learning
- Federated Learning with Correlated Data: Taming the Tail for Age-Optimal Industrial IoT
- Wireless Federated Langevin Monte Carlo: Repurposing Channel Noise for Bayesian Sampling and Privacy
- Fed-TGAN: Federated Learning Framework for Synthesizing Tabular Data
- Learning Federated Representations and Recommendations with Limited Negatives
- Federated Variational Learning for Anomaly Detection in Multivariate Time Series
- Fair and Consistent Federated Learning
- Towards More Efficient Federated Learning with Better Optimization Objects
- Multi-Center Federated Learning
- Order Optimal One-Shot Federated Learning for non-Convex Loss Functions
- Client Selection Approach in Support of Clustered Federated Learning over Wireless Edge Networks
- Communication-Efficient Federated Learning via Robust Distributed Mean Estimation
- Elastic scattering of slow electrons by carbon nanotubes
- Cross-Silo Federated Learning for Multi-Tier Networks with Vertical and Horizontal Data Partitioning
- Federated Distributionally Robust Optimization for Phase Configuration of RISs
- FedSkel: Efficient Federated Learning on Heterogeneous Systems with Skeleton Gradients Update
- Mobility-Aware Cluster Federated Learning in Hierarchical Wireless Networks
- Accelerating Federated Learning with a Global Biased Optimiser
- SemiFed: Semi-supervised Federated Learning with Consistency and Pseudo-Labeling
- Personalised Federated Learning: A Combinational Approach
- Flexible Clustered Federated Learning for Client-Level Data Distribution Shift
- Anarchic Federated Learning
- Federated Learning Meets Fairness and Differential Privacy
- Back to the Drawing Board: A Critical Evaluation of Poisoning Attacks on Federated Learning
- Federated Multi-Task Learning under a Mixture of Distributions
- Data-Free Evaluation of User Contributions in Federated Learning
- Federated Learning for UAV Swarms Under Class Imbalance and Power Consumption Constraints
- Federated Learning for Open Banking
- Federated Learning for Privacy-Preserving Open Innovation Future on Digital Health
- PIVODL: Privacy-preserving vertical federated learning over distributed labels
- Byzantine Fault-Tolerance in Federated Local SGD under 2f-Redundancy
- Enabling SQL-based Training Data Debugging for Federated Learning
- Federated Reinforcement Learning: Techniques, Applications, and Open Challenges
- Targeting Underrepresented Populations in Precision Medicine: A Federated Transfer Learning Approach
- A Survey and Comparative Study on Multi-Cloud Architectures: Emerging Issues And Challenges For Cloud Federation
- Private Multi-Task Learning: Formulation and Applications to Federated Learning
- Unit-Modulus Wireless Federated Learning Via Penalty Alternating Minimization
- FedKD: Communication Efficient Federated Learning via Knowledge Distillation
- Energy-Efficient Massive MIMO for Serving Multiple Federated Learning Groups
- GRP-FED: Addressing Client Imbalance in Federated Learning via Global-Regularized Personalization
- Federated Reconnaissance: Efficient, Distributed, Class-Incremental Learning
- Asynchronous Federated Learning for Sensor Data with Concept Drift
- Federated Learning: Issues in Medical Application
- FLASHE: Additively Symmetric Homomorphic Encryption for Cross-Silo Federated Learning
- Statistical Estimation and Inference via Local SGD in Federated Learning
- Ground-Assisted Federated Learning in LEO Satellite Constellations
- FedApp: a Research Sandbox for Application Orchestration in Federated Clouds using OpenStack
- GTG-Shapley: Efficient and Accurate Participant Contribution Evaluation in Federated Learning
- Fair Federated Learning for Heterogeneous Face Data
- Reconfigurable Intelligent Surface Empowered Over-the-Air Federated Edge Learning
- On Second-order Optimization Methods for Federated Learning
- Practical and Secure Federated Recommendation with Personalized Masks
- Generation of Synthetic Electronic Health Records Using a Federated GAN
- Federated Learning Beyond the Star: Local D2D Model Consensus with Global Cluster Sampling
- FedZKT: Zero-Shot Knowledge Transfer towards Heterogeneous On-Device Models in Federated Learning
- Iterated Vector Fields and Conservatism, with Applications to Federated Learning
- System Optimization in Synchronous Federated Training: A Survey
- An Experimental Study of Class Imbalance in Federated Learning
- A distillation-based approach integrating continual learning and federated learning for pervasive services
- Asynchronous Federated Learning on Heterogeneous Devices: A Survey
- FedCon: A Contrastive Framework for Federated Semi-Supervised Learning
- Multimodal Federated Learning
- Utility Fairness for the Differentially Private Federated Learning
- On the Initial Behavior Monitoring Issues in Federated Learning
- Cost-Effective Federated Learning in Mobile Edge Networks
- Efficient-FedRec: Efficient Federated Learning Framework for Privacy-Preserving News Recommendation
- Federated Ensemble Model-based Reinforcement Learning
- FedTriNet: A Pseudo Labeling Method with Three Players for Federated Semi-supervised Learning
- Source Inference Attacks in Federated Learning
- FedFair: Training Fair Models In Cross-Silo Federated Learning
- AMI-FML: A Privacy-Preserving Federated Machine Learning Framework for AMI
- Exploiting Heterogeneity in Robust Federated Best-Arm Identification
- Federating Scholarly Infrastructures with GraphQL
- SignGuard: Byzantine-robust Federated Learning through Collaborative Malicious Gradient Filtering
- Concept Drift Detection in Federated Networked Systems
- Bayesian AirComp with Sign-Alignment Precoding for Wireless Federated Learning
- A Blockchain based Federated Learning for Message Dissemination in Vehicular Networks
- Fast Federated Edge Learning with Overlapped Communication and Computation and Channel-Aware Fair Client Scheduling
- Hierarchical Electricity and Carbon Trading in Transmission and Distribution Networks Based on Virtual Federated Prosumer
- Federated Learning of Molecular Properties in a Heterogeneous Setting
- Federated Contrastive Learning for Decentralized Unlabeled Medical Images
- Federated Submodel Averaging
- OpenFed: A Comprehensive and Versatile Open-Source Federated Learning Framework
- Personalized Federated Learning for Heterogeneous Clients with Clustered Knowledge Transfer
- Achieving Model Fairness in Vertical Federated Learning
- Comfetch: Federated Learning of Large Networks on Memory-Constrained Clients via Sketching
- Enforcing fairness in private federated learning via the modified method of differential multipliers
- AsySQN: Faster Vertical Federated Learning Algorithms with Better Computation Resource Utilization
- MixNN: Protection of Federated Learning Against Inference Attacks by Mixing Neural Network Layers
- Federated Deep Learning with Bayesian Privacy
- FedIPR: Ownership Verification for Federated Deep Neural Network Models
- Toward Efficient Federated Learning in Multi-Channeled Mobile Edge Network with Layerd Gradient Compression
- Improving Fairness for Data Valuation in Federated Learning
- DeSMP: Differential Privacy-exploited Stealthy Model Poisoning Attacks in Federated Learning
- Backdoor Attacks on Federated Learning with Lottery Ticket Hypothesis
- In-network Computation for Large-scale Federated Learning over Wireless Edge Networks
- Federated Feature Selection for Cyber-Physical Systems of Systems
- A Generative Federated Learning Framework for Differential Privacy
- Aristotle Cloud Federation: Container Runtimes Technical Report
- FedProc: Prototypical Contrastive Federated Learning on Non-IID data
- Federated Learning Algorithms for Generalized Mixed-effects Model (GLMM) on Horizontally Partitioned Data from Distributed Sources
- LightSecAgg: Rethinking Secure Aggregation in Federated Learning
- Federated Learning over Next-Generation Ethernet Passive Optical Networks
- Federated Self-Supervised Contrastive Learning via Ensemble Similarity Distillation
- Opportunistic Federation of CubeSat Constellations: a Game-Changing Paradigm Enabling Enhanced IoT Services in the Sky
- Federated Learning in ASR: Not as Easy as You Think
- Coding for Straggler Mitigation in Federated Learning
- Federated Dropout -- A Simple Approach for Enabling Federated Learning on Resource Constrained Devices
- Lightweight Transformer in Federated Setting for Human Activity Recognition
- Personalized Retrogress-Resilient Framework for Real-World Medical Federated Learning
- Asynchronous Upper Confidence Bound Algorithms for Federated Linear Bandits
- FairFed: Enabling Group Fairness in Federated Learning
- SecFL: Confidential Federated Learning using TEEs
- TinyFedTL: Federated Transfer Learning on Tiny Devices
- MedPerf: Open Benchmarking Platform for Medical Artificial Intelligence using Federated Evaluation
- Privacy enabled Financial Text Classification using Differential Privacy and Federated Learning
- Federating for Learning Group Fair Models
- Secure Aggregation for Buffered Asynchronous Federated Learning
- Blockchain-based Federated Learning: A Comprehensive Survey
- Securing Federated Learning: A Covert Communication-based Approach
- Communication-Efficient Federated Learning with Binary Neural Networks
- FedDQ: Communication-Efficient Federated Learning with Descending Quantization
- Federated Distillation of Natural Language Understanding with Confident Sinkhorns
- SSFL: Tackling Label Deficiency in Federated Learning via Personalized Self-Supervision
- Federated Learning via Plurality Vote
- Two-Bit Aggregation for Communication Efficient and Differentially Private Federated Learning
- Automatic Tuning of Federated Learning Hyper-Parameters from System Perspective
- Towards Federated Learning-Enabled Visible Light Communication in 6G Systems
- Efficient and Private Federated Learning with Partially Trainable Networks
- Federated Learning from Small Datasets
- Federated Learning for Big Data: A Survey on Opportunities, Applications, and Future Directions
- FSL: Federated Supermask Learning
- Enabling On-Device Training of Speech Recognition Models with Federated Dropout
- Neural Tangent Kernel Empowered Federated Learning
- The Skellam Mechanism for Differentially Private Federated Learning
- Gradual Federated Learning with Simulated Annealing
- Dual Attention-Based Federated Learning for Wireless Traffic Prediction
- ProgFed: Effective, Communication, and Computation Efficient Federated Learning by Progressive Training
- Partial Variable Training for Efficient On-Device Federated Learning
- Deep Federated Learning for Autonomous Driving
- Privacy-Preserving Phishing Email Detection Based on Federated Learning and LSTM
- Federated Natural Language Generation for Personalized Dialogue System
- Graph-Fraudster: Adversarial Attacks on Graph Neural Network Based Vertical Federated Learning
- Communication-Efficient Online Federated Learning Framework for Nonlinear Regression
- WAFFLE: Weighted Averaging for Personalized Federated Learning
- Federated Learning Over Cellular-Connected UAV Networks with Non-IID Datasets
- FedMM: Saddle Point Optimization for Federated Adversarial Domain Adaptation
- Blockchain and Federated Edge Learning for Privacy-Preserving Mobile Crowdsensing
- Federated Learning for COVID-19 Detection with Generative Adversarial Networks in Edge Cloud Computing
- FedSpeech: Federated Text-to-Speech with Continual Learning
- Resource-constrained Federated Edge Learning with Heterogeneous Data: Formulation and Analysis
- Federated learning and next generation wireless communications: A survey on bidirectional relationship
- Sim-to-Real Transfer in Multi-agent Reinforcement Networking for Federated Edge Computing
- Distribution-Free Federated Learning with Conformal Predictions
- FedSEAL: Semi-Supervised Federated Learning with Self-Ensemble Learning and Negative Learning
- FedMe: Federated Learning via Model Exchange
- Federated Route Leak Detection in Inter-domain Routing with Privacy Guarantee
- Evaluation of Hyperparameter-Optimization Approaches in an Industrial Federated Learning System
- Nothing Wasted: Full Contribution Enforcement in Federated Edge Learning
- FedSLD: Federated Learning with Shared Label Distribution for Medical Image Classification
- Adapt to Adaptation: Learning Personalization for Cross-Silo Federated Learning
- Semi-asynchronous Hierarchical Federated Learning for Cooperative Intelligent Transportation Systems
- Towards General Deep Leakage in Federated Learning
- Towards Federated Bayesian Network Structure Learning with Continuous Optimization
- BEV-SGD: Best Effort Voting SGD for Analog Aggregation Based Federated Learning against Byzantine Attackers
- Tackling Dynamics in Federated Incremental Learning with Variational Embedding Rehearsal
- User-Centric Federated Learning
- FedHe: Heterogeneous Models and Communication-Efficient Federated Learning
- TsmoBN: Interventional Generalization for Unseen Clients in Federated Learning
- TESSERACT: Gradient Flip Score to Secure Federated Learning Against Model Poisoning Attacks
- A Federated Learning Aggregation Algorithm for Pervasive Computing: Evaluation and Comparison
- Fidel: Reconstructing Private Training Samples from Weight Updates in Federated Learning
- Architectural Patterns for the Design of Federated Learning Systems
- Robust Blockchained Federated Learning with Model Validation and Proof-of-Stake Inspired Consensus
- Federated Learning Based Proactive Handover in Millimeter-wave Vehicular Networks
- Collaborative Federated Learning For Healthcare: Multi-Modal COVID-19 Diagnosis at the Edge
- Vertical federated learning based on DFP and BFGS
- Failure Prediction in Production Line Based on Federated Learning: An Empirical Study
- Self-supervised Cross-silo Federated Neural Architecture Search
- FedChain: Secure Proof-of-Stake-based Framework for Federated-blockchain Systems
- Battery-constrained Federated Edge Learning in UAV-enabled IoT for B5G/6G Networks
- Gain without Pain: Offsetting DP-injected Nosies Stealthily in Cross-device Federated Learning
- FEDZIP: A Compression Framework for Communication-Efficient Federated Learning
- Bias-Variance Reduced Local SGD for Less Heterogeneous Federated Learning
- Multi-Tier Federated Learning for Vertically Partitioned Data
- Stragglers Are Not Disaster: A Hybrid Federated Learning Algorithm with Delayed Gradients
- Strong exciton-photon coupling with colloidal quantum dots in a tuneable microcavity
- Enhancing WiFi Multiple Access Performance with Federated Deep Reinforcement Learning
- Achieving Linear Convergence in Federated Learning under Objective and Systems Heterogeneity
- FedU: A Unified Framework for Federated Multi-Task Learning with Laplacian Regularization
- On the Impact of Device and Behavioral Heterogeneity in Federated Learning
- A Federated Data-Driven Evolutionary Algorithm
- When Crowdsensing Meets Federated Learning: Privacy-Preserving Mobile Crowdsensing System
- Multiple Kernel-Based Online Federated Learning
- Federated Edge Learning with Misaligned Over-The-Air Computation
- Scalable federated machine learning with FEDn
- Secure Bilevel Asynchronous Vertical Federated Learning with Backward Updating
- Privacy Amplification for Federated Learning via User Sampling and Wireless Aggregation
- Federated Functional Gradient Boosting
- An Experiment Study on Federated LearningTestbed
- Opportunistic Federated Learning: An Exploration of Egocentric Collaboration for Pervasive Computing Applications
- Prior-Free Auctions for the Demand Side of Federated Learning
- On the Convergence Time of Federated Learning Over Wireless Networks Under Imperfect CSI
- Empowering Prosumer Communities in Smart Grid with Wireless Communications and Federated Edge Learning
- Joint Optimization of Communications and Federated Learning Over the Air
- Fed-DDM: A Federated Ledgers based Framework for Hierarchical Decentralized Data Marketplaces
- FedGraphNN: A Federated Learning System and Benchmark for Graph Neural Networks
- Federated Learning for Internet of Things: A Comprehensive Survey
- Research on Resource Allocation for Efficient Federated Learning
- Federated Learning for Malware Detection in IoT Devices
- Auto-FedAvg: Learnable Federated Averaging for Multi-Institutional Medical Image Segmentation
- Blockchain based Privacy-Preserved Federated Learning for Medical Images: A Case Study of COVID-19 CT Scans
- Confined Gradient Descent: Privacy-preserving Optimization for Federated Learning
- Towards On-Device Federated Learning: A Direct Acyclic Graph-based Blockchain Approach
- Secure and Efficient Federated Learning Through Layering and Sharding Blockchain
- FedProto: Federated Prototype Learning over Heterogeneous Devices
- A Federated Learning Framework for Non-Intrusive Load Monitoring
- FedPandemic: A Cross-Device Federated Learning Approach Towards Elementary Prognosis of Diseases During a Pandemic
- On-device Federated Learning with Flower
- Bayesian Variational Federated Learning and Unlearning in Decentralized Networks
- Communication-Efficient Agnostic Federated Averaging
- FL-AGCNS: Federated Learning Framework for Automatic Graph Convolutional Network Search
- Threshold-Based Data Exclusion Approach for Energy-Efficient Federated Edge Learning
- Sample-based and Feature-based Federated Learning via Mini-batch SSCA
- Communication Efficient Federated Learning with Adaptive Quantization
- Towards Causal Federated Learning For Enhanced Robustness and Privacy
- Federated Generalized Face Presentation Attack Detection
- BROADCAST: Reducing Both Stochastic and Compression Noise to Robustify Communication-Efficient Federated Learning
- Privacy-preserving Federated Learning based on Multi-key Homomorphic Encryption
- Resource Rationing for Wireless Federated Learning: Concept, Benefits, and Challenges
- Federated Learning-based Active Authentication on Mobile Devices
- D-Cliques: Compensating NonIIDness in Decentralized Federated Learning with Topology
- The Role of Cross-Silo Federated Learning in Facilitating Data Sharing in the Agri-Food Sector
- Incentive Mechanism Design for Federated Learning: Hedonic Game Approach
- Federated Intrusion Detection for IoT with Heterogeneous Cohort Privacy
- Transparent Contribution Evaluation for Secure Federated Learning on Blockchain
- Achieving Linear Speedup with Partial Worker Participation in Non-IID Federated Learning
- FedH2L: Federated Learning with Model and Statistical Heterogeneity
- Dopamine: Differentially Private Federated Learning on Medical Data
- Federated Multi-Armed Bandits
- Differential Privacy Meets Federated Learning under Communication Constraints
- Federated Learning over Wireless Device-to-Device Networks: Algorithms and Convergence Analysis
- Scaling Federated Learning for Fine-tuning of Large Language Models
- Decentralized Federated Learning Preserves Model and Data Privacy
- Federated Learning on Non-IID Data Silos: An Experimental Study
- SAFELearning: Enable Backdoor Detectability In Federated Learning With Secure Aggregation
- FedAUX: Leveraging Unlabeled Auxiliary Data in Federated Learning
- Learning Rate Optimization for Federated Learning Exploiting Over-the-air Computation
- DEAL: Decremental Energy-Aware Learning in a Federated System
- Estimation of Microphone Clusters in Acoustic Sensor Networks using Unsupervised Federated Learning
- Federated Reconstruction: Partially Local Federated Learning
- Distributed Spectrum and Power Allocation for D2D-U Networks: A Scheme based on NN and Federated Learning
- Federated Acoustic Modeling For Automatic Speech Recognition
- Adaptive Quantization of Model Updates for Communication-Efficient Federated Learning
- Federated Deep AUC Maximization for Heterogeneous Data with a Constant Communication Complexity
- Robust Federated Learning with Attack-Adaptive Aggregation
- Meta Federated Learning
- Privacy-Preserving Self-Taught Federated Learning for Heterogeneous Data
- Efficient Algorithms for Federated Saddle Point Optimization
- Federated Learning in Smart Cities: A Comprehensive Survey
- FedProf: Optimizing Federated Learning with Dynamic Data Profiling
- Federated Dropout Learning for Hybrid Beamforming With Spatial Path Index Modulation In Multi-User mmWave-MIMO Systems
- A first look into the carbon footprint of federated learning
- Federated Learning over Wireless Networks: A Band-limited Coordinated Descent Approach
- Scaling Neuroscience Research using Federated Learning
- Federated Evaluation and Tuning for On-Device Personalization: System Design & Applications
- Federated Depression Detection from Multi-SourceMobile Health Data
- Making a Case for Federated Learning in the Internet of Vehicles and Intelligent Transportation Systems
- CFLMEC: Cooperative Federated Learning for Mobile Edge Computing
- Mobility-Aware Routing and Caching: A Federated Learning Assisted Approach
- Clustering Algorithm to Detect Adversaries in Federated Learning
- Federated $f$-Differential Privacy
- Sustainable Federated Learning
- QuPeL: Quantized Personalization with Applications to Federated Learning
- FedCom: A Byzantine-Robust Local Model Aggregation Rule Using Data Commitment for Federated Learning
- Personalized Semi-Supervised Federated Learning for Human Activity Recognition
- Efficient Ring-topology Decentralized Federated Learning with Deep Generative Models for Industrial Artificial Intelligent
- CSAFL: A Clustered Semi-Asynchronous Federated Learning Framework
- FedNLP: A Research Platform for Federated Learning in Natural Language Processing
- FedSAE: A Novel Self-Adaptive Federated Learning Framework in Heterogeneous Systems
- Decentralized Federated Learning for UAV Networks: Architecture, Challenges, and Opportunities
- An Overview of Federated Learning at the Edge and Distributed Ledger Technologies for Robotic and Autonomous Systems
- Gradient Masked Federated Optimization
- Federated Traffic Synthesizing and Classification Using Generative Adversarial Networks
- A Survey on Federated Learning and its Applications for Accelerating Industrial Internet of Things
- Covert Channel Attack to Federated Learning Systems
- Federated Double Deep Q-learning for Joint Delay and Energy Minimization in IoT networks
- Decentralized Federated Averaging
- Leveraging Sharing Communities to Achieve Federated Learning for Cybersecurity
- Wireless Federated Learning (WFL) for 6G Networks -- Part II: The Compute-then-Transmit NOMA Paradigm
- Communication-Efficient Federated Learning with Dual-Side Low-Rank Compression
- Communication-Efficient and Personalized Federated Lottery Ticket Learning
- Semi-Decentralized Federated Edge Learning for Fast Convergence on Non-IID Data
- Simultaneous Wireless Information and Power Transfer for Federated Learning
- End-to-End Speech Recognition from Federated Acoustic Models
- Multi-resource allocation for federated settings: A non-homogeneous Markov chain model
- A Graph Federated Architecture with Privacy Preserving Learning
- Pronto: Federated Task Scheduling
- Federated Identity Management (FIdM) Systems Limitation And Solutions
- From Distributed Machine Learning to Federated Learning: A Survey
- PPFL: Privacy-preserving Federated Learning with Trusted Execution Environments
- Privacy-Preserving Federated Learning on Partitioned Attributes
- Personalized Federated Learning by Structured and Unstructured Pruning under Data Heterogeneity
- Wireless Federated Learning (WFL) for 6G Networks -- Part I: Research Challenges and Future Trends
- Federated Face Recognition
- Loss Tolerant Federated Learning
- Stronger Privacy for Federated Collaborative Filtering with Implicit Feedback
- Latency Analysis of Consortium Blockchained Federated Learning
- Slashing Communication Traffic in Federated Learning by Transmitting Clustered Model Updates
- Separate but Together: Unsupervised Federated Learning for Speech Enhancement from Non-IID Data
- Federated Unbiased Learning to Rank
- FL-NTK: A Neural Tangent Kernel-based Framework for Federated Learning Convergence Analysis
- An Efficient Learning Framework For Federated XGBoost Using Secret Sharing And Distributed Optimization
- The FeatureCloud AI Store for Federated Learning in Biomedicine and Beyond
- The Federated Tumor Segmentation (FeTS) Challenge
- Clustered Sampling: Low-Variance and Improved Representativity for Clients Selection in Federated Learning
- Federated Learning with Unreliable Clients: Performance Analysis and Mechanism Design
- Node Selection Toward Faster Convergence for Federated Learning on Non-IID Data
- EasyFL: A Low-code Federated Learning Platform For Dummies
- Differentially Private Federated Knowledge Graphs Embedding
- Federated Learning With Highly Imbalanced Audio Data
- Private Hierarchical Clustering in Federated Networks
- A Privacy-Preserving Approach to Extraction of Personal Information through Automatic Annotation and Federated Learning
- Fed-EINI: An Efficient and Interpretable Inference Framework for Decision Tree Ensembles in Federated Learning
- Data-Free Knowledge Distillation for Heterogeneous Federated Learning
- Energy Minimized Federated Fog Computing over Passive Optical Networks
- HyFed: A Hybrid Federated Framework for Privacy-preserving Machine Learning
- Byzantine-Resilient Federated Machine Learning via Over-the-Air Computation
- Fast Federated Learning by Balancing Communication Trade-Offs
- Fed-NILM: A Federated Learning-based Non-Intrusive Load Monitoring Method for Privacy-Protection
- Federated Graph Learning -- A Position Paper
- FedScale: Benchmarking Model and System Performance of Federated Learning
- Designing ECG Monitoring Healthcare System with Federated Transfer Learning and Explainable AI
- Networked Federated Multi-Task Learning
- Federated Meta Learning Enhanced Acoustic Radio Cooperative Framework for Ocean of Things Underwater Acoustic Communications
- Federated Learning for Short-term Residential Energy Demand Forecasting
- PPT: A Privacy-Preserving Global Model Training Protocol for Federated Learning in P2P Networks
- FED-$χ^2$: Privacy Preserving Federated Correlation Test
- Federated Learning for Industrial Internet of Things in Future Industries
- Towards a Federated Learning Framework for Heterogeneous Devices of Internet of Things
- On Dynamic Resource Allocation for Blockchain Assisted Federated Learning over Wireless Channels
- Energy-Efficient and Federated Meta-Learning via Projected Stochastic Gradient Ascent
- Unifying Distillation with Personalization in Federated Learning
- Quantum Federated Learning with Quantum Data
- H-FL: A Hierarchical Communication-Efficient and Privacy-Protected Architecture for Federated Learning
- Federated Estimation of Causal Effects from Observational Data
- Dynamic Scheduling for Over-the-Air Federated Edge Learning with Energy Constraints
- Wireless Federated Learning with Limited Communication and Differential Privacy
- Meta-HAR: Federated Representation Learning for Human Activity Recognition
- QLSD: Quantised Langevin stochastic dynamics for Bayesian federated learning
- FedHealth 2: Weighted Federated Transfer Learning via Batch Normalization for Personalized Healthcare
- FedHybrid: A Hybrid Primal-Dual Algorithm Framework for Federated Optimization
- SemiFL: Communication Efficient Semi-Supervised Federated Learning with Unlabeled Clients
- Local Adaptivity in Federated Learning: Convergence and Consistency
- FedCCEA : A Practical Approach of Client Contribution Evaluation for Federated Learning
- Securing Secure Aggregation: Mitigating Multi-Round Privacy Leakage in Federated Learning
- Unsupervised Clustered Federated Learning in Complex Multi-source Acoustic Environments
- Fast Federated Learning in the Presence of Arbitrary Device Unavailability
- Federated Hyperparameter Tuning: Challenges, Baselines, and Connections to Weight-Sharing
- Cross-Node Federated Graph Neural Network for Spatio-Temporal Data Modeling
- FedDICE: A ransomware spread detection in a distributed integrated clinical environment using federated learning and SDN based mitigation
- Multi-VFL: A Vertical Federated Learning System for Multiple Data and Label Owners
- FedBABU: Towards Enhanced Representation for Federated Image Classification
- Rethinking Architecture Design for Tackling Data Heterogeneity in Federated Learning
- Differentially Private Federated Learning via Inexact ADMM
- Exploiting Record Similarity for Practical Vertical Federated Learning
- Efficient and Less Centralized Federated Learning
- Joint Client Scheduling and Resource Allocation under Channel Uncertainty in Federated Learning
- Federated Learning on Non-IID Data: A Survey
- Adaptive Dynamic Pruning for Non-IID Federated Learning
- DP-NormFedAvg: Normalizing Client Updates for Privacy-Preserving Federated Learning
- FedNILM: Applying Federated Learning to NILM Applications at the Edge
- Federated Learning for Internet of Things: A Federated Learning Framework for On-device Anomaly Data Detection
- Over-the-Air Decentralized Federated Learning
- CRFL: Certifiably Robust Federated Learning against Backdoor Attacks
- STAR-RIS Enabled Heterogeneous Networks: Ubiquitous NOMA Communication and Pervasive Federated Learning
- Federated Semi-supervised Medical Image Classification via Inter-client Relation Matching
- Federated Learning over Energy Harvesting Wireless Networks
- FGLP: A Federated Fine-Grained Location Prediction System for Mobile Users
- QuantumFed: A Federated Learning Framework for Collaborative Quantum Training
- Optimized Power Control Design for Over-the-Air Federated Edge Learning
- Quantized Federated Learning under Transmission Delay and Outage Constraints
- Towards Heterogeneous Clients with Elastic Federated Learning
- Federated Learning for Intrusion Detection System: Concepts, Challenges and Future Directions
- Optimality and Stability in Federated Learning: A Game-theoretic Approach
- Zero-Shot Federated Learning with New Classes for Audio Classification
- A Vertical Federated Learning Framework for Horizontally Partitioned Labels
- Compositional Federated Learning: Applications in Distributionally Robust Averaging and Meta Learning
- A Federated Data-Driven Evolutionary Algorithm for Expensive Multi/Many-objective Optimization
- Low-Latency Federated Learning over Wireless Channels with Differential Privacy
- Implicit Gradient Alignment in Distributed and Federated Learning
- Benchmarking Differential Privacy and Federated Learning for BERT Models
- Reward-Based 1-bit Compressed Federated Distillation on Blockchain
- Federated Dynamic Spectrum Access
- Federated Learning for Intrusion Detection in IoT Security: A Hybrid Ensemble Approach
- A Comprehensive Survey of Incentive Mechanism for Federated Learning
- Personalized Federated Learning with Gaussian Processes
- UAV-assisted Online Machine Learning over Multi-Tiered Networks: A Hierarchical Nested Personalized Federated Learning Approach
- Faithful Edge Federated Learning: Scalability and Privacy
- Global Knowledge Distillation in Federated Learning
- FedMix: Approximation of Mixup under Mean Augmented Federated Learning
- On Bridging Generic and Personalized Federated Learning
- Segmented Federated Learning for Adaptive Intrusion Detection System
- Gradient-Leakage Resilient Federated Learning
- Byzantine-robust Federated Learning through Spatial-temporal Analysis of Local Model Updates
- Towards Scheduling Federated Deep Learning using Meta-Gradients for Inter-Hospital Learning
- Towards Node Liability in Federated Learning: Computational Cost and Network Overhead
- Differentially private federated deep learning for multi-site medical image segmentation
- DER Forecast using Privacy Preserving Federated Learning
- RoFL: Attestable Robustness for Secure Federated Learning
- Management of Resource at the Network Edge for Federated Learning
- Federated Learning with Downlink Device Selection
- Energy Efficient Federated Learning in Integrated Fog-Cloud Computing Enabled Internet-of-Things Networks
- Federated Learning as a Mean-Field Game
- Federated Learning for Multi-Center Imaging Diagnostics: A Study in Cardiovascular Disease
- A Federated Semi-Supervised Learning Approach for Network Traffic Classification
- Personalized Federated Learning over non-IID Data for Indoor Localization
- FedAdapt: Adaptive Offloading for IoT Devices in Federated Learning
- Lithography Hotspot Detection via Heterogeneous Federated Learning with Local Adaptation
- Offloading Optimization with Delay Distribution in the 3-tier Federated Cloud, Edge, and Fog Systems
- Personalized Federated Learning via Maximizing Correlation with Sparse and Hierarchical Extensions
- Leveraging a Federation of Knowledge Graphs to Improve Faceted Search in Digital Libraries
- Communication-Efficient Hierarchical Federated Learning for IoT Heterogeneous Systems with Imbalanced Data
- Wigner time delay of a particle elastically scattered by a cluster of zero-range potentials
- Federated Self-Training for Semi-Supervised Audio Recognition
- A Field Guide to Federated Optimization
- Decentralized and Personalized Federated Learning
- Genetic CFL: Optimization of Hyper-Parameters in Clustered Federated Learning
- Privacy-preserving Spatiotemporal Scenario Generation of Renewable Energies: A Federated Deep Generative Learning Approach
- Federated Whole Prostate Segmentation in MRI with Personalized Neural Architectures
- AutoFL: Enabling Heterogeneity-Aware Energy Efficient Federated Learning
- RobustFed: A Truth Inference Approach for Robust Federated Learning
- Decentralized federated learning of deep neural networks on non-iid data
- Trends in Blockchain and Federated Learning for Data Sharing in Distributed Platforms
- Federated Learning with Dynamic Transformer for Text to Speech
- RingFed: Reducing Communication Costs in Federated Learning on Non-IID Data
- Relay-Assisted Cooperative Federated Learning
- How Does Cell-Free Massive MIMO Support Multiple Federated Learning Groups?
- Precision-Weighted Federated Learning
- Defending against Reconstruction Attack in Vertical Federated Learning
- Federated Learning using Smart Contracts on Blockchains, based on Reward Driven Approach
- Fed-ensemble: Improving Generalization through Model Ensembling in Federated Learning
- Federated Learning Versus Classical Machine Learning: A Convergence Comparison
- Communication Efficiency in Federated Learning: Achievements and Challenges
- Device Scheduling and Update Aggregation Policies for Asynchronous Federated Learning
- FedLab: A Flexible Federated Learning Framework
- Federated Learning with Fair Worker Selection: A Multi-Round Submodular Maximization Approach
- Aggregate or Not? Exploring Where to Privatize in DNN Based Federated Learning Under Different Non-IID Scenes
- Preliminary Steps Towards Federated Sentiment Classification
- Decentralized Federated Learning: Balancing Communication and Computing Costs
- Federated Action Recognition on Heterogeneous Embedded Devices
- On The Impact of Client Sampling on Federated Learning Convergence
- LEGATO: A LayerwisE Gradient AggregaTiOn Algorithm for Mitigating Byzantine Attacks in Federated Learning
- Federated Learning Meets Natural Language Processing: A Survey
- New Metrics to Evaluate the Performance and Fairness of Personalized Federated Learning
- Secure Bayesian Federated Analytics for Privacy-Preserving Trend Detection
- HAFLO: GPU-Based Acceleration for Federated Logistic Regression
- QuPeD: Quantized Personalization via Distillation with Applications to Federated Learning
- Sensing and Mapping for Better Roads: Initial Plan for Using Federated Learning and Implementing a Digital Twin to Identify the Road Conditions in a Developing Country -- Sri Lanka
- A Scalable Federated Multi-agent Architecture for Networked Connected Communication Network
- Information Stealing in Federated Learning Systems Based on Generative Adversarial Networks
- Communication-Efficient Federated Learning via Predictive Coding
- Evaluating Federated Learning for Intrusion Detection in Internet of Things: Review and Challenges
- Bit-efficient Numerical Aggregation and Stronger Privacy for Trust in Federated Analytics
- Personalized Federated Learning with Clustering: Non-IID Heart Rate Variability Data Application
- FedJAX: Federated learning simulation with JAX
- Decentralized Federated Learning with Unreliable Communications
- On Addressing Heterogeneity in Federated Learning for Autonomous Vehicles Connected to a Drone Orchestrator
- GIFAIR-FL: An Approach for Group and Individual Fairness in Federated Learning
- User Scheduling for Federated Learning Through Over-the-Air Computation
- Secure Neuroimaging Analysis using Federated Learning with Homomorphic Encryption
- FederatedNILM: A Distributed and Privacy-preserving Framework for Non-intrusive Load Monitoring based on Federated Deep Learning
- Fed-BEV: A Federated Learning Framework for Modelling Energy Consumption of Battery Electric Vehicles
- ABC-FL: Anomalous and Benign client Classification in Federated Learning
- FedPAGE: A Fast Local Stochastic Gradient Method for Communication-Efficient Federated Learning
- FedMatch: Federated Learning Over Heterogeneous Question Answering Data
- A Contract Theory based Incentive Mechanism for Federated Learning
- Communication Optimization in Large Scale Federated Learning using Autoencoder Compressed Weight Updates
- Dynamic Attention-based Communication-Efficient Federated Learning
- An Operator Splitting View of Federated Learning
- Auto-weighted Robust Federated Learning with Corrupted Data Sources
- Covert Model Poisoning Against Federated Learning: Algorithm Design and Optimization
- Edge Federated Learning Via Unit-Modulus Over-The-Air Computation (Extended Version)
- Curse or Redemption? How Data Heterogeneity Affects the Robustness of Federated Learning
- Heterogeneity for the Win: One-Shot Federated Clustering
- Adversarial training in communication constrained federated learning
- FedDis: Disentangled Federated Learning for Unsupervised Brain Pathology Segmentation
- Distributed Dynamic Map Fusion via Federated Learning for Intelligent Networked Vehicles
- FedV: Privacy-Preserving Federated Learning over Vertically Partitioned Data
- Simeon -- Secure Federated Machine Learning Through Iterative Filtering
- FedGP: Correlation-Based Active Client Selection for Heterogeneous Federated Learning
- Privacy and Trust Redefined in Federated Machine Learning
- Certifiably-Robust Federated Adversarial Learning via Randomized Smoothing
- Model-Contrastive Federated Learning
- Decentralized and Model-Free Federated Learning: Consensus-Based Distillation in Function Space
- Federated Learning Meets Blockchain in Edge Computing: Opportunities and Challenges
-
2022
- Data Heterogeneity-Robust Federated Learning via Group Client Selection in Industrial IoT
- An Efficient Federated Distillation Learning System for Multi-task Time Series Classification
- Wireless-Enabled Asynchronous Federated Fourier Neural Network for Turbulence Prediction in Urban Air Mobility (UAM)
- DeepSight: Mitigating Backdoor Attacks in Federated Learning Through Deep Model Inspection
- Robust Semi-supervised Federated Learning for Images Automatic Recognition in Internet of Drones
- Towards Understanding Quality Challenges of the Federated Learning: A First Look from the Lens of Robustness
- Sample Selection with Deadline Control for Efficient Federated Learning on Heterogeneous Clients
- Federated Optimization of Smooth Loss Functions
- Auction-Based Ex-Post-Payment Incentive Mechanism Design for Horizontal Federated Learning with Reputation and Contribution Measurement
- Multi-Model Federated Learning
- Fair and efficient contribution valuation for vertical federated learning
- Optimizing the Communication-Accuracy Trade-off in Federated Learning with Rate-Distortion Theory
- A Fair and Efficient Hybrid Federated Learning Framework based on XGBoost for Distributed Power Prediction
- LoMar: A Local Defense Against Poisoning Attack on Federated Learning
- A Multi-agent Reinforcement Learning Approach for Efficient Client Selection in Federated Learning
- An Interpretable Federated Learning-based Network Intrusion Detection Framework
- FedDTG:Federated Data-Free Knowledge Distillation via Three-Player Generative Adversarial Networks
- Communication-Efficient Federated Learning with Acceleration of Global Momentum
- RFLBAT: A Robust Federated Learning Algorithm against Backdoor Attack
- Partial Model Averaging in Federated Learning: Performance Guarantees and Benefits
- Federated AirNet: Hybrid Digital-Analog Neural Network Transmission for Federated Learning
- Jamming Attacks on Federated Learning in Wireless Networks
- Demystifying Swarm Learning: A New Paradigm of Blockchain-based Decentralized Federated Learning
- Variance-Reduced Heterogeneous Federated Learning via Stratified Client Selection
- A Physical Perspective to Human Migration Phenomenon
- EFMVFL: An Efficient and Flexible Multi-party Vertical Federated Learning without a Third Party
- Fairness in Federated Learning for Spatial-Temporal Applications
- Model Transferring Attacks to Backdoor HyperNetwork in Personalized Federated Learning
- Towards Federated Clustering: A Federated Fuzzy $c$-Means Algorithm (FFCM)
- On Multi-domain Network Slicing Orchestration Architecture & Federated Resource Control
- Communication-Efficient Device Scheduling for Federated Learning Using Stochastic Optimization
- Caring Without Sharing: A Federated Learning Crowdsensing Framework for Diversifying Representation of Cities
- Survey on Federated Learning Threats: concepts, taxonomy on attacks and defences, experimental study and challenges
- Towards Energy Efficient Distributed Federated Learning for 6G Networks
- Minimax Demographic Group Fairness in Federated Learning
- Federated Learning with Heterogeneous Architectures using Graph HyperNetworks
- TOFU: Towards Obfuscated Federated Updates by Encoding Weight Updates into Gradients from Proxy Data
- Vertical Federated Edge Learning with Distributed Integrated Sensing and Communication
- Blockchain-based Collaborated Federated Learning for Improved Security, Privacy and Reliability
- FedComm: Federated Learning as a Medium for Covert Communication
- FedMed-GAN: Federated Domain Translation on Unsupervised Cross-Modality Brain Image Synthesis
- Online Auction-Based Incentive Mechanism Design for Horizontal Federated Learning with Budget Constraint
- A Comprehensive Survey on Federated Learning: Concept and Applications
- Federated Unlearning with Knowledge Distillation
- Communication-Efficient Stochastic Zeroth-Order Optimization for Federated Learning
- Towards Multi-Objective Statistically Fair Federated Learning
- Stochastic Coded Federated Learning with Convergence and Privacy Guarantees
- An Efficient and Robust System for Vertically Federated Random Forest
- Speeding up Heterogeneous Federated Learning with Sequentially Trained Superclients
- Fast Server Learning Rate Tuning for Coded Federated Dropout
- Server-Side Stepsizes and Sampling Without Replacement Provably Help in Federated Optimization
- A dual approach for federated learning
- Data-Quality Based Scheduling for Federated Edge Learning
- Electrical Load Forecasting Using Edge Computing and Federated Learning
- Clustered Vehicular Federated Learning: Process and Optimization
- Towards a Secure and Reliable Federated Learning using Blockchain
- Achieving Personalized Federated Learning with Sparse Local Models
- On the Convergence of Heterogeneous Federated Learning with Arbitrary Adaptive Online Model Pruning
- FedLite: A Scalable Approach for Federated Learning on Resource-constrained Clients
- A Secure and Efficient Federated Learning Framework for NLP
- Gradient Masked Averaging for Federated Learning
- FedGCN: Convergence and Communication Tradeoffs in Federated Training of Graph Convolutional Networks
- Improving Federated Learning Face Recognition via Privacy-Agnostic Clusters
- Random Orthogonalization for Federated Learning in Massive MIMO Systems
- Towards Fast and Accurate Federated Learning with non-IID Data for Cloud-Based IoT Applications
- Decepticons: Corrupted Transformers Breach Privacy in Federated Learning for Language Models
- DearFSAC: An Approach to Optimizing Unreliable Federated Learning via Deep Reinforcement Learning
- Communication-Efficient Consensus Mechanism for Federated Reinforcement Learning
- Heterogeneous Federated Learning via Grouped Sequential-to-Parallel Training
- Federated Learning with Erroneous Communication Links
- Securing Federated Sensitive Topic Classification against Poisoning Attacks
- Sample Optimality and All-for-all Strategies in Personalized Federated and Collaborative Learning
- Studying the Robustness of Anti-adversarial Federated Learning Models Detecting Cyberattacks in IoT Spectrum Sensors
- Federated Active Learning (F-AL): an Efficient Annotation Strategy for Federated Learning
- Factorized-FL: Agnostic Personalized Federated Learning with Kernel Factorization & Similarity Matching
- Recycling Model Updates in Federated Learning: Are Gradient Subspaces Low-Rank?
- Multi-cell Non-coherent Over-the-Air Computation for Federated Edge Learning
- Fishing for User Data in Large-Batch Federated Learning via Gradient Magnification
- Personalized Federated Learning via Convex Clustering
- Federated Learning Challenges and Opportunities: An Outlook
- Communication Efficient Federated Learning for Generalized Linear Bandits
- Federated Reinforcement Learning for Collective Navigation of Robotic Swarms
- FedSpace: An Efficient Federated Learning Framework at Satellites and Ground Stations
- Comparative assessment of federated and centralized machine learning
- Equality Is Not Equity: Proportional Fairness in Federated Learning
- Aggregation Service for Federated Learning: An Efficient, Secure, and More Resilient Realization
- Improved Information Theoretic Generalization Bounds for Distributed and Federated Learning
- A Coalition Formation Game Approach for Personalized Federated Learning
- Communication Efficient Federated Learning via Ordered ADMM in a Fully Decentralized Setting
- Privacy-preserving Speech Emotion Recognition through Semi-Supervised Federated Learning
- Energy-Aware Edge Association for Cluster-based Personalized Federated Learning
- BEAS: Blockchain Enabled Asynchronous & Secure Federated Machine Learning
- Addressing modern and practical challenges in machine learning: A survey of online federated and transfer learning
- FL_PyTorch: optimization research simulator for federated learning
- More is Better (Mostly): On the Backdoor Attacks in Federated Graph Neural Networks
- Preserving Privacy and Security in Federated Learning
- Deep Reinforcement Learning Assisted Federated Learning Algorithm for Data Management of IIoT
- APPFL: Open-Source Software Framework for Privacy-Preserving Federated Learning
- Practical Challenges in Differentially-Private Federated Survival Analysis of Medical Data
- Learnings from Federated Learning in the Real world
- SwiftAgg: Communication-Efficient and Dropout-Resistant Secure Aggregation for Federated Learning with Worst-Case Security Guarantees
- Federated Learning of Generative Image Priors for MRI Reconstruction
- Vertical Federated Learning: Challenges, Methodologies and Experiments
- ARIBA: Towards Accurate and Robust Identification of Backdoor Attacks in Federated Learning
- Techtile -- Open 6G R&D Testbed for Communication, Positioning, Sensing, WPT and Federated Learning
- FedQAS: Privacy-aware machine reading comprehension with federated learning
- PPA: Preference Profiling Attack Against Federated Learning
- FedAttack: Effective and Covert Poisoning Attack on Federated Recommendation via Hard Sampling
- Game of Privacy: Towards Better Federated Platform Collaboration under Privacy Restriction
- Personalization Improves Privacy-Accuracy Tradeoffs in Federated Optimization
- A Newton-type algorithm for federated learning based on incremental Hessian eigenvector sharing
- Blind leads Blind: A Zero-Knowledge Attack on Federated Learning
- Local Differential Privacy for Federated Learning in Industrial Settings
- On Federated Learning with Energy Harvesting Clients
- On the Convergence of Clustered Federated Learning
- Defense Strategies Toward Model Poisoning Attacks in Federated Learning: A Survey
- FLHub: a Federated Learning model sharing service
- UA-FedRec: Untargeted Attack on Federated News Recommendation
- Do Gradient Inversion Attacks Make Federated Learning Unsafe?
- OLIVE: Oblivious and Differentially Private Federated Learning on Trusted Execution Environment
- Federated Learning with Sparsified Model Perturbation: Improving Accuracy under Client-Level Differential Privacy
- Federated Graph Neural Networks: Overview, Techniques and Challenges
- Exploring Deep Reinforcement Learning-Assisted Federated Learning for Online Resource Allocation in EdgeIoT
- Federated Contrastive Learning for Dermatological Disease Diagnosis via On-device Learning
- Architecture Agnostic Federated Learning for Neural Networks
- DBT-Net: Dual-branch federative magnitude and phase estimation with attention-in-attention transformer for monaural speech enhancement
- No One Left Behind: Inclusive Federated Learning over Heterogeneous Devices
- Evaluation and Analysis of Different Aggregation and Hyperparameter Selection Methods for Federated Brain Tumor Segmentation
- Towards Verifiable Federated Learning
- Single-shot Hyper-parameter Optimization for Federated Learning: A General Algorithm & Analysis
- MMZDA: Enabling Social Welfare Maximization in Cross-Silo Federated Learning
- Federated Stochastic Gradient Descent Begets Self-Induced Momentum
- Time-Correlated Sparsification for Efficient Over-the-Air Model Aggregation in Wireless Federated Learning
- CoFED: Cross-silo Heterogeneous Federated Multi-task Learning via Co-training
- FLAME: Federated Learning Across Multi-device Environments
- Social Welfare Maximization in Cross-Silo Federated Learning
- PerFED-GAN: Personalized Federated Learning via Generative Adversarial Networks
- Differentially Private Federated Learning via Inexact ADMM with Multiple Local Updates
- FedEmbed: Personalized Private Federated Learning
- Personalized Federated Learning with Exact Stochastic Gradient Descent
- Collusion Resistant Federated Learning with Oblivious Distributed Differential Privacy
- Privacy Leakage of Adversarial Training Models in Federated Learning Systems
- A Survey on Offloading in Federated Cloud-Edge-Fog Systems with Traditional Optimization and Machine Learning
- Incentive Mechanism Design for Joint Resource Allocation in Blockchain-based Federated Learning
- Backdoor Defense in Federated Learning Using Differential Testing and Outlier Detection
- Bitwidth Heterogeneous Federated Learning with Progressive Weight Dequantization
- Towards Tailored Models on Private AIoT Devices: Federated Direct Neural Architecture Search
- Sky Computing: Accelerating Geo-distributed Computing in Federated Learning
- Robust Federated Learning with Connectivity Failures: A Semi-Decentralized Framework with Collaborative Relaying
- Partitioned Variational Inference: A Framework for Probabilistic Federated Learning
- Towards an Accountable and Reproducible Federated Learning: A FactSheets Approach
- FedCAT: Towards Accurate Federated Learning via Device Concatenation
- Graph-Assisted Communication-Efficient Ensemble Federated Learning
- Federated Online Sparse Decision Making
- Asynchronous Decentralized Federated Learning for Collaborative Fault Diagnosis of PV Stations
- Improving Response Time of Home IoT Services in Federated Learning
- FedDrive: Generalizing Federated Learning to Semantic Segmentation in Autonomous Driving
- Computational Code-Based Privacy in Coded Federated Learning
- Leveraging Channel Noise for Sampling and Privacy via Quantized Federated Langevin Monte Carlo
- A Secure and Efficient Federated Learning Framework for NLP
- Studying the Robustness of Anti-adversarial Federated Learning Models Detecting Cyberattacks in IoT Spectrum Sensors
- Factorized-FL: Agnostic Personalized Federated Learning with Kernel Factorization & Similarity Matching
- Recycling Model Updates in Federated Learning: Are Gradient Subspaces Low-Rank?
- Fishing for User Data in Large-Batch Federated Learning via Gradient Magnification
- Federated Learning of Generative Image Priors for MRI Reconstruction
- FLAME: Federated Learning Across Multi-device Environments
- Asynchronous Decentralized Federated Learning for Collaborative Fault Diagnosis of PV Stations
- Do Gradient Inversion Attacks Make Federated Learning Unsafe?
- An Efficient Federated Distillation Learning System for Multi-task Time Series Classification
- Wireless-Enabled Asynchronous Federated Fourier Neural Network for Turbulence Prediction in Urban Air Mobility (UAM)
- DeepSight: Mitigating Backdoor Attacks in Federated Learning Through Deep Model Inspection
- Robust Semi-supervised Federated Learning for Images Automatic Recognition in Internet of Drones
- Towards Understanding Quality Challenges of the Federated Learning: A First Look from the Lens of Robustness
- Sample Selection with Deadline Control for Efficient Federated Learning on Heterogeneous Clients
- Federated Optimization of Smooth Loss Functions
- Auction-Based Ex-Post-Payment Incentive Mechanism Design for Horizontal Federated Learning with Reputation and Contribution Measurement
- Multi-Model Federated Learning
- Fair and efficient contribution valuation for vertical federated learning
- Optimizing the Communication-Accuracy Trade-off in Federated Learning with Rate-Distortion Theory
- A Fair and Efficient Hybrid Federated Learning Framework based on XGBoost for Distributed Power Prediction
- LoMar: A Local Defense Against Poisoning Attack on Federated Learning
- A Multi-agent Reinforcement Learning Approach for Efficient Client Selection in Federated Learning
- An Interpretable Federated Learning-based Network Intrusion Detection Framework
- FedDTG:Federated Data-Free Knowledge Distillation via Three-Player Generative Adversarial Networks
- Communication-Efficient Federated Learning with Acceleration of Global Momentum
- RFLBAT: A Robust Federated Learning Algorithm against Backdoor Attack
- Partial Model Averaging in Federated Learning: Performance Guarantees and Benefits
- Federated AirNet: Hybrid Digital-Analog Neural Network Transmission for Federated Learning
- Jamming Attacks on Federated Learning in Wireless Networks
- Demystifying Swarm Learning: A New Paradigm of Blockchain-based Decentralized Federated Learning
- Variance-Reduced Heterogeneous Federated Learning via Stratified Client Selection
- A Physical Perspective to Human Migration Phenomenon
- EFMVFL: An Efficient and Flexible Multi-party Vertical Federated Learning without a Third Party
- Fairness in Federated Learning for Spatial-Temporal Applications
- Model Transferring Attacks to Backdoor HyperNetwork in Personalized Federated Learning
- Towards Federated Clustering: A Federated Fuzzy $c$-Means Algorithm (FFCM)
- On Multi-domain Network Slicing Orchestration Architecture & Federated Resource Control
- Communication-Efficient Device Scheduling for Federated Learning Using Stochastic Optimization
- Caring Without Sharing: A Federated Learning Crowdsensing Framework for Diversifying Representation of Cities
- Survey on Federated Learning Threats: concepts, taxonomy on attacks and defences, experimental study and challenges
- Towards Energy Efficient Distributed Federated Learning for 6G Networks
- Minimax Demographic Group Fairness in Federated Learning
- Federated Learning with Heterogeneous Architectures using Graph HyperNetworks
- Vertical Federated Edge Learning with Distributed Integrated Sensing and Communication
- Blockchain-based Collaborated Federated Learning for Improved Security, Privacy and Reliability
- FedComm: Federated Learning as a Medium for Covert Communication
- FedMed-GAN: Federated Domain Translation on Unsupervised Cross-Modality Brain Image Synthesis
- Online Auction-Based Incentive Mechanism Design for Horizontal Federated Learning with Budget Constraint
- A Comprehensive Survey on Federated Learning: Concept and Applications
- Federated Unlearning with Knowledge Distillation
- Communication-Efficient Stochastic Zeroth-Order Optimization for Federated Learning
- Towards Multi-Objective Statistically Fair Federated Learning
- Stochastic Coded Federated Learning with Convergence and Privacy Guarantees
- An Efficient and Robust System for Vertically Federated Random Forest
- Speeding up Heterogeneous Federated Learning with Sequentially Trained Superclients
- Fast Server Learning Rate Tuning for Coded Federated Dropout
- Server-Side Stepsizes and Sampling Without Replacement Provably Help in Federated Optimization
- A dual approach for federated learning
- Data-Quality Based Scheduling for Federated Edge Learning
- Electrical Load Forecasting Using Edge Computing and Federated Learning
- Clustered Vehicular Federated Learning: Process and Optimization
- Towards a Secure and Reliable Federated Learning using Blockchain
- Achieving Personalized Federated Learning with Sparse Local Models
- On the Convergence of Heterogeneous Federated Learning with Arbitrary Adaptive Online Model Pruning
- FedLite: A Scalable Approach for Federated Learning on Resource-constrained Clients
- Gradient Masked Averaging for Federated Learning
- FedGCN: Convergence and Communication Tradeoffs in Federated Training of Graph Convolutional Networks
- Improving Federated Learning Face Recognition via Privacy-Agnostic Clusters
- Random Orthogonalization for Federated Learning in Massive MIMO Systems
- Towards Fast and Accurate Federated Learning with non-IID Data for Cloud-Based IoT Applications
- Decepticons: Corrupted Transformers Breach Privacy in Federated Learning for Language Models
- DearFSAC: An Approach to Optimizing Unreliable Federated Learning via Deep Reinforcement Learning
- Communication-Efficient Consensus Mechanism for Federated Reinforcement Learning
- Heterogeneous Federated Learning via Grouped Sequential-to-Parallel Training
- Federated Learning with Erroneous Communication Links
- Securing Federated Sensitive Topic Classification against Poisoning Attacks
- Sample Optimality and All-for-all Strategies in Personalized Federated and Collaborative Learning
- Federated Active Learning (F-AL): an Efficient Annotation Strategy for Federated Learning
- Multi-cell Non-coherent Over-the-Air Computation for Federated Edge Learning
- Personalized Federated Learning via Convex Clustering
- Federated Learning Challenges and Opportunities: An Outlook
- Communication Efficient Federated Learning for Generalized Linear Bandits
- Federated Reinforcement Learning for Collective Navigation of Robotic Swarms
- FedSpace: An Efficient Federated Learning Framework at Satellites and Ground Stations
- Data Heterogeneity-Robust Federated Learning via Group Client Selection in Industrial IoT
- Comparative assessment of federated and centralized machine learning
- Equality Is Not Equity: Proportional Fairness in Federated Learning
- Aggregation Service for Federated Learning: An Efficient, Secure, and More Resilient Realization
- Improved Information Theoretic Generalization Bounds for Distributed and Federated Learning
- A Coalition Formation Game Approach for Personalized Federated Learning
- Communication Efficient Federated Learning via Ordered ADMM in a Fully Decentralized Setting
- Privacy-preserving Speech Emotion Recognition through Semi-Supervised Federated Learning
- Energy-Aware Edge Association for Cluster-based Personalized Federated Learning
- BEAS: Blockchain Enabled Asynchronous & Secure Federated Machine Learning
- Addressing modern and practical challenges in machine learning: A survey of online federated and transfer learning
- FL_PyTorch: optimization research simulator for federated learning
- More is Better (Mostly): On the Backdoor Attacks in Federated Graph Neural Networks
- Preserving Privacy and Security in Federated Learning
- Deep Reinforcement Learning Assisted Federated Learning Algorithm for Data Management of IIoT
- APPFL: Open-Source Software Framework for Privacy-Preserving Federated Learning
- Practical Challenges in Differentially-Private Federated Survival Analysis of Medical Data
- Learnings from Federated Learning in the Real world
- SwiftAgg: Communication-Efficient and Dropout-Resistant Secure Aggregation for Federated Learning with Worst-Case Security Guarantees
- Vertical Federated Learning: Challenges, Methodologies and Experiments
- ARIBA: Towards Accurate and Robust Identification of Backdoor Attacks in Federated Learning
- Techtile -- Open 6G R&D Testbed for Communication, Positioning, Sensing, WPT and Federated Learning
- FedQAS: Privacy-aware machine reading comprehension with federated learning
- PPA: Preference Profiling Attack Against Federated Learning
- FedAttack: Effective and Covert Poisoning Attack on Federated Recommendation via Hard Sampling
- Game of Privacy: Towards Better Federated Platform Collaboration under Privacy Restriction
- Personalization Improves Privacy-Accuracy Tradeoffs in Federated Optimization
- A Newton-type algorithm for federated learning based on incremental Hessian eigenvector sharing
- Blind leads Blind: A Zero-Knowledge Attack on Federated Learning
- Local Differential Privacy for Federated Learning in Industrial Settings
- On Federated Learning with Energy Harvesting Clients
- On the Convergence of Clustered Federated Learning
- Defense Strategies Toward Model Poisoning Attacks in Federated Learning: A Survey
- FLHub: a Federated Learning model sharing service
- UA-FedRec: Untargeted Attack on Federated News Recommendation
- OLIVE: Oblivious and Differentially Private Federated Learning on Trusted Execution Environment
- Federated Learning with Sparsified Model Perturbation: Improving Accuracy under Client-Level Differential Privacy
- Federated Graph Neural Networks: Overview, Techniques and Challenges
- Exploring Deep Reinforcement Learning-Assisted Federated Learning for Online Resource Allocation in EdgeIoT
- Towards Verifiable Federated Learning
- Single-shot Hyper-parameter Optimization for Federated Learning: A General Algorithm & Analysis
- MMZDA: Enabling Social Welfare Maximization in Cross-Silo Federated Learning
- Federated Contrastive Learning for Dermatological Disease Diagnosis via On-device Learning
- Architecture Agnostic Federated Learning for Neural Networks
- DBT-Net: Dual-branch federative magnitude and phase estimation with attention-in-attention transformer for monaural speech enhancement
- No One Left Behind: Inclusive Federated Learning over Heterogeneous Devices
- Evaluation and Analysis of Different Aggregation and Hyperparameter Selection Methods for Federated Brain Tumor Segmentation
- Federated Stochastic Gradient Descent Begets Self-Induced Momentum
- Time-Correlated Sparsification for Efficient Over-the-Air Model Aggregation in Wireless Federated Learning
- CoFED: Cross-silo Heterogeneous Federated Multi-task Learning via Co-training
- Social Welfare Maximization in Cross-Silo Federated Learning
- PerFED-GAN: Personalized Federated Learning via Generative Adversarial Networks
- Differentially Private Federated Learning via Inexact ADMM with Multiple Local Updates
- FedEmbed: Personalized Private Federated Learning
- Personalized Federated Learning with Exact Stochastic Gradient Descent
- Collusion Resistant Federated Learning with Oblivious Distributed Differential Privacy
- Privacy Leakage of Adversarial Training Models in Federated Learning Systems
- A Survey on Offloading in Federated Cloud-Edge-Fog Systems with Traditional Optimization and Machine Learning
- Incentive Mechanism Design for Joint Resource Allocation in Blockchain-based Federated Learning
- Backdoor Defense in Federated Learning Using Differential Testing and Outlier Detection
- Bitwidth Heterogeneous Federated Learning with Progressive Weight Dequantization
- Towards Tailored Models on Private AIoT Devices: Federated Direct Neural Architecture Search
- Sky Computing: Accelerating Geo-distributed Computing in Federated Learning
- Robust Federated Learning with Connectivity Failures: A Semi-Decentralized Framework with Collaborative Relaying
- Partitioned Variational Inference: A Framework for Probabilistic Federated Learning
- Towards an Accountable and Reproducible Federated Learning: A FactSheets Approach
- FedCAT: Towards Accurate Federated Learning via Device Concatenation
- Graph-Assisted Communication-Efficient Ensemble Federated Learning
- Federated Online Sparse Decision Making
- Improving Response Time of Home IoT Services in Federated Learning
- FedDrive: Generalizing Federated Learning to Semantic Segmentation in Autonomous Driving
- Computational Code-Based Privacy in Coded Federated Learning
- Leveraging Channel Noise for Sampling and Privacy via Quantized Federated Langevin Monte Carlo
- TOFU: Towards Obfuscated Federated Updates by Encoding Weight Updates into Gradients from Proxy Data
-
Uncategorized
-
-
Incentive Mechanism && Fairness
- Federated Learning in Mobile Edge Networks: A Comprehensive Survey
- Federated Learning for Coalition Operations
- Machine Learning Systems for Highly-Distributed and Rapidly-Growing Data
- Marculescu R. EdgeAI: A Vision for Deep Learning in IoT Era
- Federated Learning for Wireless Communications: Motivation, Opportunities and Challenges
- Privacy-Preserving Blockchain Based Federated Learning with Differential Data Sharing
- Local differential privacy and its applications: A comprehensive survey
- Federated Learning: Challenges, Methods, and Future Directions
- A Survey towards Federated Semi-supervised Learning
- Threats to Federated Learning: A Survey
- BOOK - 4): 211-407.
- A survey of local differential privacy for securing internet of vehicles - 22.
- Differential privacy techniques for cyber physical systems: a survey - 789.
- An Introduction to Communication Efficient Edge Machine Learning
- good
- A Review of Privacy Preserving Federated Learning for Private IoT Analytics
- SECure: A Social and Environmental Certificate for AI Systems
- Federated Learning for Resource-Constrained IoT Devices: Panoramas and State-of-the-art
- From Federated Learning to Fog Learning: Towards Large-Scale Distributed Machine Learning in Heterogeneous Wireless Networks
- A firm foundation for private data analysis
- Big privacy: Challenges and opportunities of privacy study in the age of big data - 2763.
- Technical privacy metrics: a systematic survey - 38.
- Demystifying parallel and distributed deep learning: An in-depth concurrency analysis - 43.
- Federated Learning Systems: Vision, Hype and Reality for Data Privacy and Protection
- Differential privacy: a survey of results
- TIST
- Federated Learning for 6G Communications: Challenges, Methods, and Future Directions
- No Peek: A Survey of private distributed deep learning
- Federated Learning in Mobile Edge Networks: A Comprehensive Survey
- Federated Learning Systems: Vision, Hype and Reality for Data Privacy and Protection
- Differential privacy: a survey of results
- Technical privacy metrics: a systematic survey - 38.
- Demystifying parallel and distributed deep learning: An in-depth concurrency analysis - 43.
- Differential privacy techniques for cyber physical systems: a survey - 789.
- TIST
- Federated Learning for Wireless Communications: Motivation, Opportunities and Challenges
- Federated Learning: Challenges, Methods, and Future Directions
- Privacy-Preserving Blockchain Based Federated Learning with Differential Data Sharing
- good
- A Review of Privacy Preserving Federated Learning for Private IoT Analytics
- From Federated Learning to Fog Learning: Towards Large-Scale Distributed Machine Learning in Heterogeneous Wireless Networks
- SECure: A Social and Environmental Certificate for AI Systems
- Local differential privacy and its applications: A comprehensive survey
- Differential privacy in new settings - first annual ACM-SIAM symposium on Discrete Algorithms. Society for Industrial and Applied Mathematics, 2010: 174-183.
- Communication-efficient edge AI: Algorithms and systems
- SoK: differential privacies
- Federated Learning for Coalition Operations
- Machine Learning Systems for Highly-Distributed and Rapidly-Growing Data
- Federated Learning for 6G Communications: Challenges, Methods, and Future Directions
- A survey of local differential privacy for securing internet of vehicles - 22.
- Federated Learning for Resource-Constrained IoT Devices: Panoramas and State-of-the-art
- A Survey towards Federated Semi-supervised Learning
- Threats to Federated Learning: A Survey
- Marculescu R. EdgeAI: A Vision for Deep Learning in IoT Era
- An Introduction to Communication Efficient Edge Machine Learning
- Survey of Personalization Techniques for Federated Learning
- The complexity of differential privacy - 450.
-
Health Care
- Federated Learning for Healthcare Informatics
- Multi-institutional deep learning modeling without sharing patient data: A feasibility study on brain tumor segmentation - 104.
- Federated Learning in Distributed Medical Databases: Meta-Analysis of Large-Scale Subcortical Brain Data
- FADL:Federated-Autonomous Deep Learning for Distributed Electronic Health Record
- LoAdaBoost:Loss-Based AdaBoost Federated Machine Learning on medical Data
- Patient Clustering Improves Efficiency of Federated Machine Learning to predict mortality and hospital stay time using distributed Electronic Medical Records
- FedHealth: A Federated Transfer Learning Framework for Wearable Healthcare
- HHHFL: Hierarchical Heterogeneous Horizontal Federated Learning for Electroencephalography
- Privacy-preserving Federated Brain Tumour Segmentation
- good
- Privacy Preserving Stochastic Channel-Based Federated Learning with Neural Network Pruning
- Differential Privacy-enabled Federated Learning for Sensitive Health Data
- Federated Uncertainty-Aware Learning for Distributed Hospital EHR Data
- A blockchain-orchestrated Federated Learning architecture for healthcare consortia
- Federated and Differentially Private Learning for Electronic Health Records
- Preserving patient privacy while training a predictive model of in-hospital mortality
- Learn Electronic Health Records by Fully Decentralized Federated Learning
- Multi-site fMRI Analysis Using Privacy-preserving Federated Learning and Domain Adaptation: ABIDE Results
- Stratified cross-validation for unbiased and privacy-preserving federated learning
- Federated machine learning with Anonymous Random Hybridization (FeARH) on medical records
- The Future of Digital Health with Federated Learning
- Federated Transfer Learning for EEG Signal Classification
- A Federated Learning Framework for Healthcare IoT devices
- Privacy-Preserving Technology to Help Millions of People: Federated Prediction Model for Stroke Prevention
- Anonymizing Data for Privacy-Preserving Federated Learning
- Privacy Preserving Stochastic Channel-Based Federated Learning with Neural Network Pruning
- Anonymizing Data for Privacy-Preserving Federated Learning
- Federated Learning for Healthcare Informatics
- Federated Learning in Distributed Medical Databases: Meta-Analysis of Large-Scale Subcortical Brain Data
- FADL:Federated-Autonomous Deep Learning for Distributed Electronic Health Record
- LoAdaBoost:Loss-Based AdaBoost Federated Machine Learning on medical Data
- Patient Clustering Improves Efficiency of Federated Machine Learning to predict mortality and hospital stay time using distributed Electronic Medical Records
- FedHealth: A Federated Transfer Learning Framework for Wearable Healthcare
- HHHFL: Hierarchical Heterogeneous Horizontal Federated Learning for Electroencephalography
- Privacy-preserving Federated Brain Tumour Segmentation
- good
- Differential Privacy-enabled Federated Learning for Sensitive Health Data
- Federated Uncertainty-Aware Learning for Distributed Hospital EHR Data
- A blockchain-orchestrated Federated Learning architecture for healthcare consortia
- Federated and Differentially Private Learning for Electronic Health Records
- Preserving patient privacy while training a predictive model of in-hospital mortality
- Learn Electronic Health Records by Fully Decentralized Federated Learning
- Multi-site fMRI Analysis Using Privacy-preserving Federated Learning and Domain Adaptation: ABIDE Results
- Stratified cross-validation for unbiased and privacy-preserving federated learning
- Federated machine learning with Anonymous Random Hybridization (FeARH) on medical records
- The Future of Digital Health with Federated Learning
- Federated Transfer Learning for EEG Signal Classification
- A Federated Learning Framework for Healthcare IoT devices
- Privacy-Preserving Technology to Help Millions of People: Federated Prediction Model for Stroke Prevention
-
Introduction && Survey
- the Connection between Cryptography and Differential Privacy: a Survey
- Convergence of Edge Computing and Deep Learning: A Comprehensive Survey
- the Connection between Cryptography and Differential Privacy: a Survey
- No Peek: A Survey of private distributed deep learning
- An Introduction to Communication Efficient Edge Machine Learning
-
Distributed Optimization
- Federated optimization: Distributed optimization beyond the datacenter
- Collaborative Deep Learning in Fixed Topology Networks
- Stochastic, Distributed and Federated Optimization for Machine Learning
- Local SGD converges fast and communicates little
- LAG: Lazily Aggregated Gradient for Communication-Efficient Distributed Learning
- CpSGD: Communication-Efficient and Differentially-Private Distributed SGD.
- Don't Use Large Mini-Batches, Use Local SGD
- Cooperative SGD: A unified framework for the design and analysis of communication-efficient SGD algorithms
- Learning Rate Adaptation for Federated and Differentially Private Learning
- Federated optimization in heterogeneous networks - 450.<br>[code:[litian96/FedProx](https://github.com/litian96/FedProx)]
- On the Convergence of Federated Optimization in Heterogeneous Networks
- Asynchronous federated optimization
- Semi-cyclic stochastic gradient descent
- Differentially private learning with adaptive clipping
- Robust Federated Learning in a Heterogeneous Environment
- Scalable and differentially private distributed aggregation in the shuffled model
- First analysis of local gd on heterogeneous data
- Gradient descent with compressed iterates
- Tighter theory for local SGD on identical and heterogeneous data - 4529.
- Communication-efficient distributed optimization in networks with gradient tracking
- Accelerating Federated Learning via Momentum Gradient Descent
- ICML - stochastic-controlled-averaging-for-federated-learning](https://slideslive.com/38927610/scaffold-stochastic-controlled-averaging-for-federated-learning)]
- On the Convergence of Local Descent Methods in Federated Learning
- Representation of Federated Learning via Worst-Case Robust Optimization Theory
- Parallel Restarted SPIDER--Communication Efficient Distributed Nonconvex Optimization with Optimal Computation Complexity
- Primal–Dual Methods for Large-Scale and Distributed Convex Optimization and Data Analytics - 1938.
- Distributed Fixed Point Methods with Compressed Iterates
- FedDANE: A Federated Newton-Type Method
- Faster On-Device Training Using New Federated Momentum Algorithm
- Federated Learning of a Mixture of Global and Local Models
- ICLR
- Distributed Non-Convex Optimization with Sublinear Speedup under Intermittent Client Availability
- Distributed Optimization over Block-Cyclic Data
- Dynamic Federated Learning
- Uncertainty Principle for Communication Compression in Distributed and Federated Learning and the Search for an Optimal Compressor
- Overlap Local-SGD: An Algorithmic Approach to Hide Communication Delays in Distributed SGD
- Personalized Federated Learning for Intelligent IoT Applications: A Cloud-Edge based Framework
- Device Heterogeneity in Federated Learning: A Superquantile Approach
- LASG: Lazily Aggregated Stochastic Gradients for Communication-Efficient Distributed Learning
- ICML - for-compressed-gradient-descent-in-distributed-optimization)]
- Federated Residual Learning
- ICML - local-sgd-to-local-fixed-point-methods-for-federated-learning)]
- Distributed Stochastic Non-Convex Optimization: Momentum-Based Variance Reduction
- NIPS
- Paschalidis I C. Local SGD With a Communication Overhead Depending Only on the Number of Workers
- A Primal-Dual SGD Algorithm for Distributed Nonconvex Optimization
- STL-SGD: Speeding Up Local SGD with Stagewise Communication Period
- NIPS - NeurIPS20](https://github.com/hongliny/FedAc-NeurIPS20)]
- Communication-Efficient Robust Federated Learning Over Heterogeneous Datasets
- DEED: A General Quantization Scheme for Communication Efficiency in Bits
- Exact Support Recovery in Federated Regression with One-shot Communication
- Local Stochastic Approximation: A Unified View of Federated Learning and Distributed Multi-Task Reinforcement Learning Algorithms
- Baseline
- FLAP -- A Federated Learning Framework for Attribute-based Access Control Policies
- Collaborative Deep Learning in Fixed Topology Networks
- Local SGD converges fast and communicates little
- Tighter theory for local SGD on identical and heterogeneous data - 4529.
- Primal–Dual Methods for Large-Scale and Distributed Convex Optimization and Data Analytics - 1938.
- Overlap Local-SGD: An Algorithmic Approach to Hide Communication Delays in Distributed SGD
- Adaptive Federated Learning in Resource Constrained Edge Computing Systems
- Federated optimization: Distributed optimization beyond the datacenter
- Stochastic, Distributed and Federated Optimization for Machine Learning
- Don't Use Large Mini-Batches, Use Local SGD
- Cooperative SGD: A unified framework for the design and analysis of communication-efficient SGD algorithms
- Learning Rate Adaptation for Federated and Differentially Private Learning
- On the Convergence of Federated Optimization in Heterogeneous Networks
- Asynchronous federated optimization
- Semi-cyclic stochastic gradient descent
- Differentially private learning with adaptive clipping
- Robust Federated Learning in a Heterogeneous Environment
- Scalable and differentially private distributed aggregation in the shuffled model
- First analysis of local gd on heterogeneous data
- Gradient descent with compressed iterates
- Communication-efficient distributed optimization in networks with gradient tracking
- Accelerating Federated Learning via Momentum Gradient Descent
- ICML - stochastic-controlled-averaging-for-federated-learning](https://slideslive.com/38927610/scaffold-stochastic-controlled-averaging-for-federated-learning)]
- On the Convergence of Local Descent Methods in Federated Learning
- Representation of Federated Learning via Worst-Case Robust Optimization Theory
- Parallel Restarted SPIDER--Communication Efficient Distributed Nonconvex Optimization with Optimal Computation Complexity
- Distributed Fixed Point Methods with Compressed Iterates
- FedDANE: A Federated Newton-Type Method
- Faster On-Device Training Using New Federated Momentum Algorithm
- Federated Learning of a Mixture of Global and Local Models
- ICLR
- Distributed Non-Convex Optimization with Sublinear Speedup under Intermittent Client Availability
- Distributed Optimization over Block-Cyclic Data
- Dynamic Federated Learning
- Uncertainty Principle for Communication Compression in Distributed and Federated Learning and the Search for an Optimal Compressor
- Personalized Federated Learning for Intelligent IoT Applications: A Cloud-Edge based Framework
- Device Heterogeneity in Federated Learning: A Superquantile Approach
- LASG: Lazily Aggregated Stochastic Gradients for Communication-Efficient Distributed Learning
- ICML - for-compressed-gradient-descent-in-distributed-optimization)]
- Baseline
- Federated Residual Learning
- ICML - local-sgd-to-local-fixed-point-methods-for-federated-learning)]
- Distributed Stochastic Non-Convex Optimization: Momentum-Based Variance Reduction
- NIPS
- Paschalidis I C. Local SGD With a Communication Overhead Depending Only on the Number of Workers
- A Primal-Dual SGD Algorithm for Distributed Nonconvex Optimization
- STL-SGD: Speeding Up Local SGD with Stagewise Communication Period
- NIPS - NeurIPS20](https://github.com/hongliny/FedAc-NeurIPS20)]
- Communication-Efficient Robust Federated Learning Over Heterogeneous Datasets
- DEED: A General Quantization Scheme for Communication Efficiency in Bits
- Exact Support Recovery in Federated Regression with One-shot Communication
- Local Stochastic Approximation: A Unified View of Federated Learning and Distributed Multi-Task Reinforcement Learning Algorithms
- On the outsized importance of learning rates in local update methods
- Baseline
- FLAP -- A Federated Learning Framework for Attribute-based Access Control Policies
-
Hierarchical Federated Learning && Horizontal Federated Learning
- LM
- NN - federated-neural-matching](https://github.com/IBM/probabilistic-federated-neural-matching)]
- NN
- Edge-Assisted Hierarchical Federated Learning with Non-IID Data
- LM,NN
- HFEL: Joint Edge Association and Resource Allocation for Cost-Efficient Hierarchical Federated Edge Learning
- NN
- NN
- LM
- LM,NN
- Federated learning with hierarchical clustering of local updates to improve training on non-IID data
- LM,NN
- NN - federated-neural-matching](https://github.com/IBM/probabilistic-federated-neural-matching)]
- LM
- LM,NN
- NN
- Federated learning with hierarchical clustering of local updates to improve training on non-IID data
- LM,DT,NN
- LM
- NN
- NN
- Edge-Assisted Hierarchical Federated Learning with Non-IID Data
- LM,NN
- HFEL: Joint Edge Association and Resource Allocation for Cost-Efficient Hierarchical Federated Edge Learning
-
Communication-Efficiency
- Partitioned variational inference: A unified framework encompassing federated and continual learning
- Federated Learning with Compression: Unified Analysis and Sharp Guarantees
- good
- Multi-objective Evolutionary Federated Learning
- Intermittent Pulling with Local Compensation for Communication-Efficient Federated Learning
- Deep Gradient Compression: Reducing the Communication Bandwidth for Distributed Training
- good
- Communication-Efficient Federated Deep Learning with Asynchronous Model Update and Temporally Weighted Aggregation
- Decentralized Federated Learning: A Segmented Gossip Approach
- Detailed comparison of communication efficiency of split learning and federated learning
- SAFA: a Semi-Asynchronous Protocol for Fast Federated Learning with Low Overhead
- High-Dimensional Stochastic Gradient Quantization for Communication-Efficient Edge Learning
- Gradient Sparification for Asynchronous Distributed Training
- L-FGADMM: Layer-Wise Federated Group ADMM for Communication Efficient Decentralized Deep Learning
- Hyper-Sphere Quantization: Communication-Efficient SGD for Federated Learning
- FedOpt: Towards Communication Efficiency and Privacy Preservation in Federated Learning
- RPN: A Residual Pooling Network for Efficient Federated Learning
- Communication-efficient decentralized learning with sparsification and adaptive peer selection
- Gradient Statistics Aware Power Control for Over-the-Air Federated Learning in Fading Channels
- Ternary Compression for Communication-Efficient Federated Learning
- Dynamic Sampling and Selective Masking for Communication-Efficient Federated Learning
- Evaluating the Communication Efficiency in Federated Learning Algorithms
- Federated Learning With Quantized Global Model Updates
- A Better Alternative to Error Feedback for Communication-Efficient Distributed Learning
- Scheduling Policy and Power Allocation for Federated Learning in NOMA Based MEC
- Artemis: tight convergence guarantees for bidirectional compression in Federated Learning
- Federated Mutual Learning
- One-Shot Federated Learning
- A Better Alternative to Error Feedback for Communication-Efficient Distributed Learning
- One-Shot Federated Learning
- Federated Learning with Compression: Unified Analysis and Sharp Guarantees
- Partitioned variational inference: A unified framework encompassing federated and continual learning
- Communication-Efficient Federated Deep Learning with Asynchronous Model Update and Temporally Weighted Aggregation
- Decentralized Federated Learning: A Segmented Gossip Approach
- Detailed comparison of communication efficiency of split learning and federated learning
- SAFA: a Semi-Asynchronous Protocol for Fast Federated Learning with Low Overhead
- good
- Gradient Sparification for Asynchronous Distributed Training
- L-FGADMM: Layer-Wise Federated Group ADMM for Communication Efficient Decentralized Deep Learning
- Hyper-Sphere Quantization: Communication-Efficient SGD for Federated Learning
- Multi-objective Evolutionary Federated Learning
- good
- Intermittent Pulling with Local Compensation for Communication-Efficient Federated Learning
- RPN: A Residual Pooling Network for Efficient Federated Learning
- Communication-efficient decentralized learning with sparsification and adaptive peer selection
- Gradient Statistics Aware Power Control for Over-the-Air Federated Learning in Fading Channels
- Ternary Compression for Communication-Efficient Federated Learning
- Dynamic Sampling and Selective Masking for Communication-Efficient Federated Learning
- Evaluating the Communication Efficiency in Federated Learning Algorithms
- Federated Learning With Quantized Global Model Updates
- Scheduling Policy and Power Allocation for Federated Learning in NOMA Based MEC
- Artemis: tight convergence guarantees for bidirectional compression in Federated Learning
- Federated Mutual Learning
-
Non-IID and Model Personalization
- Federated Learning with Non-IID Data
- Hybrid-FL for wireless networks: Cooperative learning mechanism using non-IID data - 2020 IEEE International Conference on Communications (ICC). IEEE, 2020: 1-7.
- Distributed training with heterogeneous data: Bridging median-and mean-based algorithms
- Astraea: Self-balancing Federated Learning for Improving Classification Accuracy of Mobile Deep Learning Applications
- ICLR
- Multi-hop Federated Private Data Augmentation with Sample Compression
- Measure Contribution of Participants in Federated Learning
- Improving Federated Learning Personalization via Model Agnostic Meta Learning
- The non-iid data quagmire of decentralized machine learning - 4398.
- Clustered Federated Learning: Model-Agnostic Distributed Multi-Task Optimization under Privacy Constraints
- Overcoming Forgetting in Federated Learning on Non-IID Data
- Federated Evaluation of On-device Personalization
- ICLR
- Federated Learning with Personalization Layers
- Robust Federated Learning Through Representation Matching and Adaptive Hyper-parameters
- Think Locally, Act Globally: Federated Learning with Local and Global Representations
- A Collaborative Learning Framework via Federated Meta-Learning
- Data Selection for Federated Learning with Relevant and Irrelevant Data at Clients
- FOCUS: Dealing with Label Quality Disparity in Federated Learning
- Salvaging Federated Learning by Local Adaptation
- Towards Federated Learning: Robustness Analytics to Data Heterogeneity
- Personalized Federated Learning: A Meta-Learning Approach
- Three Approaches for Personalization with Applications to Federated Learning
- Semi-Federated Learning
- Adaptive Personalized Federated Learning
- FedMAX: Mitigating Activation Divergence for Accurate and Communication-Efficient Federated Learning
- ICML - learning-with-only-positive-labels](https://slideslive.com/38928322/federated-learning-with-only-positive-labels)]
- Multi-Center Federated Learning
- Global Multiclass Classification from Heterogeneous Local Models
- FedPD: A Federated Learning Framework with Optimal Rates and Adaptivity to Non-IID Data
- Towards Efficient Scheduling of Federated Mobile Devices under Computational and Statistical Heterogeneity
- Continual Local Training for Better Initialization of Federated Models
- NIPS
- XOR Mixup: Privacy-Preserving Data Augmentation for One-Shot Federated Learning
- Towards Flexible Device Participation in Federated Learning for Non-IID Data
- NIPS
- NIPS
- FedCD: Improving Performance in non-IID Federated Learning
- FedFMC: Sequential Efficient Federated Learning on Non-iid Data
- Client Adaptation improves Federated Learning with Simulated Non-IID Clients
- NIPS
- Federated Learning with Unbiased Gradient Aggregation and Controllable Meta Updating
- Distributed training with heterogeneous data: Bridging median-and mean-based algorithms
- Federated Learning with Unbiased Gradient Aggregation and Controllable Meta Updating
- Federated Learning with Non-IID Data
- Hybrid-FL for wireless networks: Cooperative learning mechanism using non-IID data - 2020 IEEE International Conference on Communications (ICC). IEEE, 2020: 1-7.
- Astraea: Self-balancing Federated Learning for Improving Classification Accuracy of Mobile Deep Learning Applications
- ICLR
- Multi-hop Federated Private Data Augmentation with Sample Compression
- Measure Contribution of Participants in Federated Learning
- Improving Federated Learning Personalization via Model Agnostic Meta Learning
- Clustered Federated Learning: Model-Agnostic Distributed Multi-Task Optimization under Privacy Constraints
- Overcoming Forgetting in Federated Learning on Non-IID Data
- Federated Evaluation of On-device Personalization
- ICLR
- Federated Learning with Personalization Layers
- Robust Federated Learning Through Representation Matching and Adaptive Hyper-parameters
- Think Locally, Act Globally: Federated Learning with Local and Global Representations
- A Collaborative Learning Framework via Federated Meta-Learning
- Data Selection for Federated Learning with Relevant and Irrelevant Data at Clients
- FOCUS: Dealing with Label Quality Disparity in Federated Learning
- Salvaging Federated Learning by Local Adaptation
- Towards Federated Learning: Robustness Analytics to Data Heterogeneity
- Personalized Federated Learning: A Meta-Learning Approach
- Three Approaches for Personalization with Applications to Federated Learning
- Semi-Federated Learning
- Adaptive Personalized Federated Learning
- FedMAX: Mitigating Activation Divergence for Accurate and Communication-Efficient Federated Learning
- ICML - learning-with-only-positive-labels](https://slideslive.com/38928322/federated-learning-with-only-positive-labels)]
- Multi-Center Federated Learning
- Global Multiclass Classification from Heterogeneous Local Models
- FedPD: A Federated Learning Framework with Optimal Rates and Adaptivity to Non-IID Data
- Towards Efficient Scheduling of Federated Mobile Devices under Computational and Statistical Heterogeneity
- Continual Local Training for Better Initialization of Federated Models
- NIPS
- XOR Mixup: Privacy-Preserving Data Augmentation for One-Shot Federated Learning
- Towards Flexible Device Participation in Federated Learning for Non-IID Data
- NIPS
- NIPS
- FedCD: Improving Performance in non-IID Federated Learning
- FedFMC: Sequential Efficient Federated Learning on Non-iid Data
- Client Adaptation improves Federated Learning with Simulated Non-IID Clients
- NIPS
-
Computer Vision
- Measuring the Effects of Non-Identical Data Distribution for Federated Visual Classification
- FedVision: An Online Visual Object Detection Platform Powered by Federated Learning
- CVPR - research/federated_vision_datasets](https://github.com/google-research/google-research/tree/master/federated_vision_datasets)]
- Federated Face Anti-spoofing
- Measuring the Effects of Non-Identical Data Distribution for Federated Visual Classification
- FedVision: An Online Visual Object Detection Platform Powered by Federated Learning
- CVPR - research/federated_vision_datasets](https://github.com/google-research/google-research/tree/master/federated_vision_datasets)]
- Federated Face Anti-spoofing
-
Semi-Supervised Learning
-
Vertical Federated Learning
- Entity Resolution and Federated Learning get a Federated Resolution
- DT
- Parallel Distributed Logistic Regression for Vertical Federated Learning without Third-Party Coordinator
- A Quasi-Newton Method Based Vertical Federated Learning Framework for Logistic Regression
- A Communication Efficient Vertical Federated Learning Framework
- Multi-Participant Multi-Class Vertical Federated Learning
- Asymmetrical Vertical Federated Learning
- Entity Resolution and Federated Learning get a Federated Resolution
- DT
- Parallel Distributed Logistic Regression for Vertical Federated Learning without Third-Party Coordinator
- A Quasi-Newton Method Based Vertical Federated Learning Framework for Logistic Regression
- A Communication Efficient Vertical Federated Learning Framework
- Multi-Participant Multi-Class Vertical Federated Learning
- Asymmetrical Vertical Federated Learning
- VAFL: a Method of Vertical Asynchronous Federated Learning
-
Federated Transfer Learning
- good
- Wireless Federated Distillation for Distributed Edge Learning with Heterogeneous Data
- Knowledge Federation: Hierarchy and Unification
- Federated Reinforcement Distillation with Proxy Experience Memory
- FedMD: Heterogenous Federated Learning via Model Distillation
- Secure and Efficient Federated Transfer Learning
- Cooperative Learning via Federated Distillation over Fading Channels
- Communication-Efficient On-Device Machine Learning: Federated Distillation and Augmentation under Non-IID Private Data
- Proxy Experience Replay: Federated Distillation for Distributed Reinforcement Learning
- Communication-Efficient On-Device Machine Learning: Federated Distillation and Augmentation under Non-IID Private Data
- good
- Wireless Federated Distillation for Distributed Edge Learning with Heterogeneous Data
- Federated Reinforcement Distillation with Proxy Experience Memory
- FedMD: Heterogenous Federated Learning via Model Distillation
- Secure and Efficient Federated Transfer Learning
- Cooperative Learning via Federated Distillation over Fading Channels
- Knowledge Federation: Hierarchy and Unification
- Proxy Experience Replay: Federated Distillation for Distributed Reinforcement Learning
-
Privacy && Homomorphic Encryption
- Practical secure aggregation for privacy-preserving machine learning - 1191.
- A Hybrid Approach to Privacy-Preserving Federated Learning
- Federated Generative Privacy
- Enhancing Privacy via Hierarchical Federated Learning
- Decentralized Differentially Private Segmentation with PATE
- NIPS
- Learning differentially private recurrent language models
- good
- ICML - group/ModelPoisoning](https://github.com/inspire-group/ModelPoisoning)]
- Reducing leakage in distributed deep learning for sensitive health data
- Privacy-preserving collaborative deep learning with unreliable participants - 1500.
- Federated Learning with Differential Privacy: Algorithms and Performance Analysis
- Enhancing the Privacy of Federated Learning with Sketching
- Federated Learning with Bayesian Differential Privacy
- HybridAlpha: An Efficient Approach for Privacy-Preserving Federated Learning
- Private Federated Learning with Domain Adaptation
- iDLG: Improved Deep Leakage from Gradients
- Gs-wgan: A gradient-sanitized approach for learning differentially private generators
- Privacy-preserving deep learning computation for geo-distributed medical big-data platforms - S). IEEE, 2019: 3-4.
- Practical and Bilateral Privacy-preserving Federated Learning
- FedSel: Federated SGD under Local Differential Privacy with Top-k Dimension Selection
- Decentralized Policy-Based Private Analytics
- Learn to Forget: User-Level Memorization Elimination in Federated Learning
- PrivFL: Practical Privacy-preserving Federated Regressions on High-dimensional Data over Mobile Networks
- Differentially Private AirComp Federated Learning with Power Adaptation Harnessing Receiver Noise
- Local Differential Privacy based Federated Learning for Internet of Things
- Privacy Preserving Distributed Machine Learning with Federated Learning
- Exploring Private Federated Learning with Laplacian Smoothing
- Information-Theoretic Bounds on the Generalization Error and Privacy Leakage in Federated Learning
- Efficient Privacy Preserving Edge Computing Framework for Image Classification
- A Distributed Trust Framework for Privacy-Preserving Machine Learning
- LDP-Fed: Federated Learning with Local Differential Privacy
- Secure Byzantine-Robust Machine Learning
- Privacy For Free: Wireless Federated Learning Via Uncoded Transmission With Adaptive Power Control
- Distributed Differentially Private Averaging with Improved Utility and Robustness to Malicious Parties
- Comprehensive Privacy Analysis of Deep Learning: Stand-alone and Federated Learning under Passive and Active White-box Inference Attacks
- Beyond Inferring Class Representatives: User-Level Privacy Leakage From Federated Learning
- Deep leakage from gradients - 14784.
- good
- Private federated learning on vertically partitioned data via entity resolution and additively homomorphic encryption
- ICML - group/ModelPoisoning](https://github.com/inspire-group/ModelPoisoning)]
- Federated Generative Privacy
- Enhancing Privacy via Hierarchical Federated Learning
- Private federated learning on vertically partitioned data via entity resolution and additively homomorphic encryption
- Beyond Inferring Class Representatives: User-Level Privacy Leakage From Federated Learning
- Comprehensive Privacy Analysis of Deep Learning: Stand-alone and Federated Learning under Passive and Active White-box Inference Attacks
- A Hybrid Approach to Privacy-Preserving Federated Learning
- good
- Practical secure aggregation for privacy-preserving machine learning - 1191.
- Decentralized Differentially Private Segmentation with PATE
- NIPS
- Learning differentially private recurrent language models
- good
- Reducing leakage in distributed deep learning for sensitive health data
- Privacy-preserving collaborative deep learning with unreliable participants - 1500.
- Federated Learning with Differential Privacy: Algorithms and Performance Analysis
- Enhancing the Privacy of Federated Learning with Sketching
- Federated Learning with Bayesian Differential Privacy
- HybridAlpha: An Efficient Approach for Privacy-Preserving Federated Learning
- Private Federated Learning with Domain Adaptation
- iDLG: Improved Deep Leakage from Gradients
- Privacy-preserving deep learning computation for geo-distributed medical big-data platforms - S). IEEE, 2019: 3-4.
- Practical and Bilateral Privacy-preserving Federated Learning
- FedSel: Federated SGD under Local Differential Privacy with Top-k Dimension Selection
- Decentralized Policy-Based Private Analytics
- Learn to Forget: User-Level Memorization Elimination in Federated Learning
- PrivFL: Practical Privacy-preserving Federated Regressions on High-dimensional Data over Mobile Networks
- Differentially Private AirComp Federated Learning with Power Adaptation Harnessing Receiver Noise
- Local Differential Privacy based Federated Learning for Internet of Things
- Privacy Preserving Distributed Machine Learning with Federated Learning
- Exploring Private Federated Learning with Laplacian Smoothing
- Information-Theoretic Bounds on the Generalization Error and Privacy Leakage in Federated Learning
- Efficient Privacy Preserving Edge Computing Framework for Image Classification
- LDP-Fed: Federated Learning with Local Differential Privacy
- Privacy For Free: Wireless Federated Learning Via Uncoded Transmission With Adaptive Power Control
-
Recommendation System
- Federated Meta-Learning for Recommendation
- Meta Matrix Factorization for Federated Rating Predictions - 990.
- Federating Recommendations Using Differentially Private Prototypes
- FedRec: Privacy-Preserving News Recommendation with Federated Learning
- Federated Multi-view Matrix Factorization for Personalized Recommendations
- Federated Recommendation System via Differential Privacy
- Robust Federated Recommendation System
- Secure Federated Matrix Factorization
- Federated Collaborative Filtering for Privacy-Preserving Personalized Recommendation System
- Federated Hierarchical Hybrid Networks for Clickbait Detection
- Secure Federated Matrix Factorization
- Federated Hierarchical Hybrid Networks for Clickbait Detection
- Federating Recommendations Using Differentially Private Prototypes
- FedRec: Privacy-Preserving News Recommendation with Federated Learning
- Federated Multi-view Matrix Factorization for Personalized Recommendations
- Federated Recommendation System via Differential Privacy
- Robust Federated Recommendation System
- Federated Meta-Learning for Recommendation
- Federated Collaborative Filtering for Privacy-Preserving Personalized Recommendation System
-
Transportation
- Distributed Federated Learning for Ultra-Reliable Low-Latency Vehicular Communications
- Federated Learning for Ultra-Reliable Low-Latency V2V Communications
- Energy Demand Prediction with Federated Learning for Electric Vehicle Networks
- Federated Transfer Reinforcement Learning for Autonomous Driving
- Federated Learning for Localization: A Privacy-Preserving Crowdsourcing Method
- Practical Privacy Preserving POI Recommendation
- FedLoc: Federated Learning Framework for Cooperative Localization and Location Data Processing
- Communication-Efficient Massive UAV Online Path Control: Federated Learning Meets Mean-Field Game Theory
- Privacy-preserving Traffic Flow Prediction: A Federated Learning Approach
- Beyond privacy regulations: an ethical approach to data usage in transportation
- Federated Learning Meets Contract Theory: Energy-Efficient Framework for Electric Vehicle Networks
- Towards Federated Learning in UAV-Enabled Internet of Vehicles: A Multi-Dimensional Contract-Matching Approach
- Federated Learning for Vehicular Networks
- Practical Privacy Preserving POI Recommendation
- Federated Learning for Ultra-Reliable Low-Latency V2V Communications
- Energy Demand Prediction with Federated Learning for Electric Vehicle Networks
- Federated Transfer Reinforcement Learning for Autonomous Driving
- Federated Learning for Localization: A Privacy-Preserving Crowdsourcing Method
- FedLoc: Federated Learning Framework for Cooperative Localization and Location Data Processing
- Communication-Efficient Massive UAV Online Path Control: Federated Learning Meets Mean-Field Game Theory
- Privacy-preserving Traffic Flow Prediction: A Federated Learning Approach
- Beyond privacy regulations: an ethical approach to data usage in transportation
- Federated Learning Meets Contract Theory: Energy-Efficient Framework for Electric Vehicle Networks
- Towards Federated Learning in UAV-Enabled Internet of Vehicles: A Multi-Dimensional Contract-Matching Approach
- Federated Learning for Vehicular Networks
- Distributed Federated Learning for Ultra-Reliable Low-Latency Vehicular Communications
-
Finance && Blockchain
- On-Device Federated Learning via Blockchain and its Latency Analysis
- Towards Federated Graph Learning for Collaborative Financial Crimes Detection
- FedCoin: A Peer-to-Peer Payment System for Federated Learning
- Towards Federated Graph Learning for Collaborative Financial Crimes Detection
- FedCoin: A Peer-to-Peer Payment System for Federated Learning
- On-Device Federated Learning via Blockchain and its Latency Analysis
-
Wireless Communication && Cloud Computing && networking
- In-Edge AI: Intelligentizing Mobile Edge Computing, Caching and Communication by Federated Learning
- Hierarchical Federated Learning Across Heterogeneous Cellular Networks
- CoLearn: enabling federated learning in MUD-compliant IoT edge networks - 30.
- Adaptive Task Allocation for Asynchronous Federated Mobile Edge Learning
- Joint Service Pricing and Cooperative Relay Communication for Federated Learning
- Federated Echo State Learning for Minimizing Breaks in Presence in Wireless Virtual Reality Networks
- Low-Latency Broadband Analog Aggregation for Federated Edge Learning
- Federated Learning via Over-the-Air Computation
- Federated learning over wireless networks: Optimization model design and analysis - IEEE Conference on Computer Communications. IEEE, 2019: 1387-1395.
- Machine learning at the wireless edge: Distributed stochastic gradient descent over-the-air - 2169.
- Interpret Federated Learning with Shapley Values
- Active learning solution on distributed edge computing
- Mobile Edge Computing, Blockchain and Reputation-based Crowdsourcing IoT Federated Learning: A Secure, Decentralized and Privacy-preserving System
- Energy-Efficient Radio Resource Allocation for Federated Edge Learning
- Federated Learning over Wireless Fading Channels
- A Federated Learning Approach for Mobile Packet Classification
- Federated Learning with Additional Mechanisms on Clients to Reduce Communication Costs
- Scheduling Policies for Federated Learning in Wireless Networks
- On Safeguarding Privacy and Security in the Framework of Federated Learning
- A Joint Learning and Communications Framework for Federated Learning over Wireless Networks
- Cell-Free Massive MIMO for Wireless Federated Learning
- Active Federated Learning
- FedPAQ: A Communication-Efficient Federated Learning Method with Periodic Averaging and Quantization
- Reliable Federated Learning for Mobile Networks
- Resource Allocation in Mobility-Aware Federated Learning Networks: A Deep Reinforcement Learning Approach
- Federated Learning over Wireless Networks: Convergence Analysis and Resource Allocation
- Age-Based Scheduling Policy for Federated Learning in Mobile Edge Networks
- Energy-Aware Analog Aggregation for Federated Learning with Redundant Data
- Device Scheduling with Fast Convergence for Wireless Federated Learning
- Energy Efficient Federated Learning Over Wireless Communication Networks
- Bandwidth Slicing to Boost Federated Learning in Edge Computing
- Federated Learning with Autotuned Communication-Efficient Secure Aggregation
- Federated learning with multichannel ALOHA
- Asynchronous Federated Learning with Differential Privacy for Edge Intelligence
- Federated Learning with Cooperating Devices: A Consensus Approach for Massive IoT Networks
- One-Bit Over-the-Air Aggregation for Communication-Efficient Federated Edge Learning: Design and Convergence Analysis
- Convergence Time Optimization for Federated Learning over Wireless Networks
- Communication Efficient Federated Learning over Multiple Access Channels
- Update Aware Device Scheduling for Federated Learning at the Wireless Edge
- Learning from Peers at the Wireless Edge - 784.
- Wireless Federated Learning with Local Differential Privacy
- Federated Learning in the Sky: Joint Power Allocation and Scheduling with UAV Swarms
- Decentralized Federated Learning via SGD over Wireless D2D Networks
- Federated Over-the-Air Subspace Learning from Incomplete Data
- Energy-Efficient Federated Edge Learning with Joint Communication and Computation Design
- Performance Analysis and Optimization in Privacy-Preserving Federated Learning
- Adaptive Federated Learning With Gradient Compression in Uplink NOMA
- Gradient Estimation for Federated Learning over Massive MIMO Communication Systems
- Federated Learning for Task and Resource Allocation in Wireless High Altitude Balloon Networks
- Scheduling in Cellular Federated Edge Learning with Importance and Channel Awareness
- A Blockchain-based Decentralized Federated Learning Framework with Committee Consensus
- Resource Management for Blockchain-enabled Federated Learning: A Deep Reinforcement Learning Approach
- Client Selection and Bandwidth Allocation in Wireless Federated Learning Networks: A Long-Term Perspective
- Federated Machine Learning for Intelligent IoT via Reconfigurable Intelligent Surface
- On the Design of Communication Efficient Federated Learning over Wireless Networks
- Federated Dynamic GNN with Secure Aggregation
- Network-Aware Optimization of Distributed Learning for Fog Computing
- Optimizing Over-the-Air Computation in IRS-Aided C-RAN Systems
- Towards Ubiquitous AI in 6G with Federated Learning
- Lightwave Power Transfer for Federated Learning-based Wireless Networks
- Federated Learning and Wireless Communications
- A Secure Federated Learning Framework for 5G Networks
- Efficient Federated Learning over Multiple Access Channel with Differential Privacy Constraints
- Federated Deep Learning Framework For Hybrid Beamforming in mm-Wave Massive MIMO
- Wireless Communications for Collaborative Federated Learning in the Internet of Things
- UVeQFed: Universal Vector Quantization for Federated Learning
- Mix2FLD: Downlink Federated Learning After Uplink Federated Distillation With Two-Way Mixup
- Democratizing the Edge: A Pervasive Edge Computing Framework
- Differentially Private Federated Learning for Resource-Constrained Internet of Things
- Secure Federated Learning in 5G Mobile Networks
- Learning from Peers at the Wireless Edge - 784.
- CoLearn: enabling federated learning in MUD-compliant IoT edge networks - 30.
- In-Edge AI: Intelligentizing Mobile Edge Computing, Caching and Communication by Federated Learning
- Hierarchical Federated Learning Across Heterogeneous Cellular Networks
- Secure Federated Learning in 5G Mobile Networks
- Differentially Private Federated Learning for Resource-Constrained Internet of Things
- Adaptive Task Allocation for Asynchronous Federated Mobile Edge Learning
- Joint Service Pricing and Cooperative Relay Communication for Federated Learning
- Federated Echo State Learning for Minimizing Breaks in Presence in Wireless Virtual Reality Networks
- Low-Latency Broadband Analog Aggregation for Federated Edge Learning
- Federated Learning via Over-the-Air Computation
- Machine learning at the wireless edge: Distributed stochastic gradient descent over-the-air - 2169.
- Interpret Federated Learning with Shapley Values
- Active learning solution on distributed edge computing
- Mobile Edge Computing, Blockchain and Reputation-based Crowdsourcing IoT Federated Learning: A Secure, Decentralized and Privacy-preserving System
- Energy-Efficient Radio Resource Allocation for Federated Edge Learning
- Federated Learning over Wireless Fading Channels
- A Federated Learning Approach for Mobile Packet Classification
- Federated Learning with Additional Mechanisms on Clients to Reduce Communication Costs
- Scheduling Policies for Federated Learning in Wireless Networks
- On Safeguarding Privacy and Security in the Framework of Federated Learning
- A Joint Learning and Communications Framework for Federated Learning over Wireless Networks
- Cell-Free Massive MIMO for Wireless Federated Learning
- Active Federated Learning
- FedPAQ: A Communication-Efficient Federated Learning Method with Periodic Averaging and Quantization
- Reliable Federated Learning for Mobile Networks
- Resource Allocation in Mobility-Aware Federated Learning Networks: A Deep Reinforcement Learning Approach
- Federated Learning over Wireless Networks: Convergence Analysis and Resource Allocation
- Age-Based Scheduling Policy for Federated Learning in Mobile Edge Networks
- Energy-Aware Analog Aggregation for Federated Learning with Redundant Data
- Device Scheduling with Fast Convergence for Wireless Federated Learning
- Energy Efficient Federated Learning Over Wireless Communication Networks
- Bandwidth Slicing to Boost Federated Learning in Edge Computing
- Federated Learning with Autotuned Communication-Efficient Secure Aggregation
- Federated learning with multichannel ALOHA
- Asynchronous Federated Learning with Differential Privacy for Edge Intelligence
- Federated Learning with Cooperating Devices: A Consensus Approach for Massive IoT Networks
- One-Bit Over-the-Air Aggregation for Communication-Efficient Federated Edge Learning: Design and Convergence Analysis
- Convergence Time Optimization for Federated Learning over Wireless Networks
- Communication Efficient Federated Learning over Multiple Access Channels
- Update Aware Device Scheduling for Federated Learning at the Wireless Edge
- Wireless Federated Learning with Local Differential Privacy
- Federated Learning in the Sky: Joint Power Allocation and Scheduling with UAV Swarms
- Decentralized Federated Learning via SGD over Wireless D2D Networks
- Federated Over-the-Air Subspace Learning from Incomplete Data
- Energy-Efficient Federated Edge Learning with Joint Communication and Computation Design
- Performance Analysis and Optimization in Privacy-Preserving Federated Learning
- Adaptive Federated Learning With Gradient Compression in Uplink NOMA
- Gradient Estimation for Federated Learning over Massive MIMO Communication Systems
- Federated Learning for Task and Resource Allocation in Wireless High Altitude Balloon Networks
- Scheduling in Cellular Federated Edge Learning with Importance and Channel Awareness
- A Blockchain-based Decentralized Federated Learning Framework with Committee Consensus
- Resource Management for Blockchain-enabled Federated Learning: A Deep Reinforcement Learning Approach
- Client Selection and Bandwidth Allocation in Wireless Federated Learning Networks: A Long-Term Perspective
- Federated Machine Learning for Intelligent IoT via Reconfigurable Intelligent Surface
- On the Design of Communication Efficient Federated Learning over Wireless Networks
- Federated Dynamic GNN with Secure Aggregation
- Network-Aware Optimization of Distributed Learning for Fog Computing
- Optimizing Over-the-Air Computation in IRS-Aided C-RAN Systems
- Towards Ubiquitous AI in 6G with Federated Learning
- Lightwave Power Transfer for Federated Learning-based Wireless Networks
- Federated Learning and Wireless Communications
- A Secure Federated Learning Framework for 5G Networks
- Efficient Federated Learning over Multiple Access Channel with Differential Privacy Constraints
- Federated Deep Learning Framework For Hybrid Beamforming in mm-Wave Massive MIMO
- Wireless Communications for Collaborative Federated Learning in the Internet of Things
- UVeQFed: Universal Vector Quantization for Federated Learning
- Mix2FLD: Downlink Federated Learning After Uplink Federated Distillation With Two-Way Mixup
- Democratizing the Edge: A Pervasive Edge Computing Framework
-
Natural language Processing
- good
- Federated Learning for Keyword Spotting
- Applied Federated Learning: Improving Google Keyboard Query Suggestions
- Learning private neural language modeling with attentive aggregation - 8.<br>[code:[shaoxiongji/fed-att](https://github.com/shaoxiongji/fed-att)]
- Federated Topic Modeling
- Federated Learning Of Out-Of-Vocabulary Words
- Federated AI lets a team imagine together: Federated Learning of GANs
- Federated Learning for Emoji Prediction in a Mobile Keyboard
- Two-stage Federated Phenotyping and Patient Representation Learning
- Federated User Representation Learning
- Federated Learning of N-gram Language Models
- Federated Learning for Ranking Browser History Suggestions
- Federated pretraining and fine tuning of BERT using clinical notes from multiple silos
- FedNER: Privacy-preserving Medical Named Entity Recognition with Federated Learning
- Pretraining Federated Text Models for Next Word Prediction
- Understanding Unintended Memorization in Federated Learning
- Federated Learning for Keyword Spotting
- Applied Federated Learning: Improving Google Keyboard Query Suggestions
- Learning private neural language modeling with attentive aggregation - 8.<br>[code:[shaoxiongji/fed-att](https://github.com/shaoxiongji/fed-att)]
- Federated Learning Of Out-Of-Vocabulary Words
- Federated AI lets a team imagine together: Federated Learning of GANs
- Federated Learning for Emoji Prediction in a Mobile Keyboard
- Two-stage Federated Phenotyping and Patient Representation Learning
- Federated User Representation Learning
- Federated Learning of N-gram Language Models
- Federated Learning for Ranking Browser History Suggestions
- Federated pretraining and fine tuning of BERT using clinical notes from multiple silos
- FedNER: Privacy-preserving Medical Named Entity Recognition with Federated Learning
- Pretraining Federated Text Models for Next Word Prediction
- good
-
Reinforcement Learning && Robotics
- Lifelong Federated Reinforcement Learning: A Learning Architecture for Navigation in Cloud Robotic Systems
- Efficient Training Management for Mobile Crowd-Machine Learning: A Deep Reinforcement Learning Approach.
- good
- Federated Imitation Learning: A Privacy Considered Imitation Learning Framework for Cloud Robotic Systems with Heterogeneous Sensor Data
- Lifelong Federated Reinforcement Learning: A Learning Architecture for Navigation in Cloud Robotic Systems
- Efficient Training Management for Mobile Crowd-Machine Learning: A Deep Reinforcement Learning Approach.
- good
- Federated Imitation Learning: A Privacy Considered Imitation Learning Framework for Cloud Robotic Systems with Heterogeneous Sensor Data
-
Decentralized Federated Learning
- MATCHA: Speeding up decentralized SGD via matching decomposition sampling
- Decentralized bayesian learning over graphs
- Can decentralized algorithms outperform centralized algorithms? a case study for decentralized parallel stochastic gradient descent - 5340.
- Biscotti: A ledger for private and secure peer-to-peer machine learning
- BrainTorrent: A Peer-to-Peer Environment for Decentralized Federated Learning
- Multi-consensus Decentralized Accelerated Gradient Descent
- Central Server Free Federated Learning over Single-sided Trust Social Networks
- Can decentralized algorithms outperform centralized algorithms? a case study for decentralized parallel stochastic gradient descent - 5340.
- MATCHA: Speeding up decentralized SGD via matching decomposition sampling
- Central Server Free Federated Learning over Single-sided Trust Social Networks
- Biscotti: A ledger for private and secure peer-to-peer machine learning
- BrainTorrent: A Peer-to-Peer Environment for Decentralized Federated Learning
- Decentralized bayesian learning over graphs
- Multi-consensus Decentralized Accelerated Gradient Descent
-
Adversarial-Attack-and-Defense
- Boosting Privately: Privacy-Preserving Federated Extreme Boosting for Mobile Crowdsensing
- Attack-Resistant Federated Learning with Residual-based Reweighting
- Deep models under the GAN: information leakage from collaborative deep learning - 618.
- ICLR - secure/DBA](https://github.com/AI-secure/DBA)]
- Byzantine-robust distributed learning: Towards optimal statistical rates
- Exploiting unintended feature leakage in collaborative learning - 706. <br>[code:[csong27/property-inference-collaborative-ml](https://github.com/csong27/property-inference-collaborative-ml)]
- Mitigating Sybils in Federated Learning Poisoning
- RSA: Byzantine-robust stochastic aggregation methods for distributed learning from heterogeneous datasets - 1551.
- Dancing in the dark: private multi-party machine learning in an untrusted setting
- NIPS
- AAAI
- Secure distributed on-device learning networks with Byzantine adversaries - 187.
- An End-to-End Encrypted Neural Network for Gradient Updates Transmission in Federated Learning
- Byzantine-Robust Federated Machine Learning through Adaptive Model Averaging
- Quantification of the Leakage in Federated Learning
- Eavesdrop the Composition Proportion of Training Labels in Federated Learning
- Abnormal Client Behavior Detection in Federated Learning
- Robust Federated Learning with Noisy Communication
- good
- Local Model Poisoning Attacks to Byzantine-Robust Federated Learning
- Free-riders in Federated Learning: Attacks and Defenses
- Towards Deep Federated Defenses Against Malware in Cloud Ecosystems
- Robust Aggregation for Federated Learning
- Learning to Detect Malicious Clients for Robust Federated Learning
- Stochastic-Sign SGD for Federated Learning with Theoretical Guarantees
- BASGD: Buffered Asynchronous SGD for Byzantine Learning
- Privacy-preserving Weighted Federated Learning within Oracle-Aided MPC Framework
- NIPS
- An Overview of Federated Deep Learning Privacy Attacks and Defensive Strategies
- Towards Realistic Byzantine-Robust Federated Learning
- Data Poisoning Attacks on Federated Machine Learning
- A Framework for Evaluating Gradient Leakage Attacks in Federated Learning
- Exploiting Defenses against GAN-Based Feature Inference Attacks in Federated Learning
- Two-Phase Multi-Party Computation Enabled Privacy-Preserving Federated Learning
- Backdoor Attacks on Federated Meta-Learning
- FedMGDA+: Federated Learning meets Multi-objective Optimization
- Byzantine-Resilient High-Dimensional SGD with Local Iterations on Heterogeneous Data
- FDA3: Federated Defense Against Adversarial Attacks for Cloud-Based IIoT Applications
- Protection Against Reconstruction and Its Applications in Private Federated Learning
- Cronus: Robust and Heterogeneous Collaborative Learning with Black-Box Knowledge Transfer
- Deep models under the GAN: information leakage from collaborative deep learning - 618.
- Boosting Privately: Privacy-Preserving Federated Extreme Boosting for Mobile Crowdsensing
- Byzantine-robust distributed learning: Towards optimal statistical rates
- Exploiting unintended feature leakage in collaborative learning - 706. <br>[code:[csong27/property-inference-collaborative-ml](https://github.com/csong27/property-inference-collaborative-ml)]
- Mitigating Sybils in Federated Learning Poisoning
- Dancing in the dark: private multi-party machine learning in an untrusted setting
- NIPS
- AAAI
- Secure distributed on-device learning networks with Byzantine adversaries - 187.
- An End-to-End Encrypted Neural Network for Gradient Updates Transmission in Federated Learning
- Byzantine-Robust Federated Machine Learning through Adaptive Model Averaging
- Quantification of the Leakage in Federated Learning
- Eavesdrop the Composition Proportion of Training Labels in Federated Learning
- Abnormal Client Behavior Detection in Federated Learning
- Robust Federated Learning with Noisy Communication
- good
- Local Model Poisoning Attacks to Byzantine-Robust Federated Learning
- Free-riders in Federated Learning: Attacks and Defenses
- Attack-Resistant Federated Learning with Residual-based Reweighting
- Towards Deep Federated Defenses Against Malware in Cloud Ecosystems
- Robust Aggregation for Federated Learning
- Learning to Detect Malicious Clients for Robust Federated Learning
- Stochastic-Sign SGD for Federated Learning with Theoretical Guarantees
- BASGD: Buffered Asynchronous SGD for Byzantine Learning
- Privacy-preserving Weighted Federated Learning within Oracle-Aided MPC Framework
- NIPS
- An Overview of Federated Deep Learning Privacy Attacks and Defensive Strategies
- Towards Realistic Byzantine-Robust Federated Learning
- Data Poisoning Attacks on Federated Machine Learning
- A Framework for Evaluating Gradient Leakage Attacks in Federated Learning
- Exploiting Defenses against GAN-Based Feature Inference Attacks in Federated Learning
- Two-Phase Multi-Party Computation Enabled Privacy-Preserving Federated Learning
- Backdoor Attacks on Federated Meta-Learning
- FedMGDA+: Federated Learning meets Multi-objective Optimization
- Byzantine-Resilient High-Dimensional SGD with Local Iterations on Heterogeneous Data
- FDA3: Federated Defense Against Adversarial Attacks for Cloud-Based IIoT Applications
- Protection Against Reconstruction and Its Applications in Private Federated Learning
- Cronus: Robust and Heterogeneous Collaborative Learning with Black-Box Knowledge Transfer
-
Neural Architecture Search
- Neural Architecture Search over Decentralized Data
- Real-time Federated Evolutionary Neural Architecture Search
- FedNAS: Federated Deep Learning via Neural Architecture Search
- Differentially-private Federated Neural Architecture Search
- From Federated Learning to Federated Neural Architecture Search: A Survey
- Direct Federated Neural Architecture Search
- Neural Architecture Search over Decentralized Data
- Real-time Federated Evolutionary Neural Architecture Search
- FedNAS: Federated Deep Learning via Neural Architecture Search
- Differentially-private Federated Neural Architecture Search
- From Federated Learning to Federated Neural Architecture Search: A Survey
- Direct Federated Neural Architecture Search
-
Continual Learning
-
Bayesian Learning
- Differentially Private Federated Variational Inference
- High Dimensional Restrictive Federated Model Selection with multi-objective Bayesian Optimization over shifted distributions
- High Dimensional Restrictive Federated Model Selection with multi-objective Bayesian Optimization over shifted distributions
- Differentially Private Federated Variational Inference
-
Models
- Differentially Private Data Generative Models.
- Distributed Dual Coordinate Ascent in General Tree Networks and Its Application in Federated Learning
- Md-gan: Multi-discriminator generative adversarial networks for distributed datasets - 877.
- Federated Forest
- Privacy preserving qoe modeling using collaborative learning - QoE Workshop on QoE-based Analysis and Management of Data Communication Networks. 2019: 13-18.
- The Tradeoff Between Privacy and Accuracy in Anomaly Detection Using Federated XGBoost
- Privacy-preserving Federated Bayesian Learning of a Generative Model for Imbalanced Classification of Clinical Data
- ICLR
- SecureGBM: Secure multi-party gradient boosting - 1321.
- Federated Clustering via Matrix Factorization Models: From Model Averaging to Gradient Sharing
- Federated Extra-Trees with Privacy Preserving
- An On-Device Federated Learning Approach for Cooperative Anomaly Detection
- Federated Generative Adversarial Learning
- Federated Survival Analysis with Discrete-Time Cox Models
- Privacy Threats Against Federated Matrix Factorization
- Practical Federated Gradient Boosting Decision Trees
- Practical Federated Gradient Boosting Decision Trees
- Distributed Dual Coordinate Ascent in General Tree Networks and Its Application in Federated Learning
- Md-gan: Multi-discriminator generative adversarial networks for distributed datasets - 877.
- Federated Forest
- Privacy preserving qoe modeling using collaborative learning - QoE Workshop on QoE-based Analysis and Management of Data Communication Networks. 2019: 13-18.
- The Tradeoff Between Privacy and Accuracy in Anomaly Detection Using Federated XGBoost
- Privacy-preserving Federated Bayesian Learning of a Generative Model for Imbalanced Classification of Clinical Data
- SecureGBM: Secure multi-party gradient boosting - 1321.
- Federated Clustering via Matrix Factorization Models: From Model Averaging to Gradient Sharing
- Federated Extra-Trees with Privacy Preserving
- An On-Device Federated Learning Approach for Cooperative Anomaly Detection
- Federated Generative Adversarial Learning
- Federated Survival Analysis with Discrete-Time Cox Models
- Privacy Threats Against Federated Matrix Factorization
- Differentially Private Data Generative Models.
-
Straggler Problem
- Coded Federated Computing in Wireless Networks with Straggling Devices and Imperfect CSI
- Information-Theoretic Perspective of Federated Learning
- Turbo-Aggregate: Breaking the Quadratic Aggregation Barrier in Secure Federated Learning
- Coded Federated Learning
- Coded Federated Computing in Wireless Networks with Straggling Devices and Imperfect CSI
- Information-Theoretic Perspective of Federated Learning
- Turbo-Aggregate: Breaking the Quadratic Aggregation Barrier in Secure Federated Learning
- Coded Federated Learning
-
Computation Efficiency
- SmartPC: Hierarchical Pace Control in Real-Time Federated Learning System - Time Systems Symposium (RTSS). IEEE, 2019: 406-418.
- Decaf: Iterative collaborative processing over the edge
- Split Learning for Health: Distributed Deep Learning without Sharing Raw Patient Data.
- Accelerating DNN Training in Wireless Federated Edge Learning System
- Towards Effective Device-Aware Federated Learning
- Model Pruning Enables Efficient Federated Learning on Edge Devices
- Federated Neuromorphic Learning of Spiking Neural Networks for Low-Power Edge Intelligence
- Asynchronous Online Federated Learning for Edge Devices
- Secure Federated Submodel Learning
- Lottery Hypothesis based Unsupervised Pre-training for Model Compression in Federated Learning
- SplitFed: When Federated Learning Meets Split Learning
- Distributed Learning on Heterogeneous Resource-Constrained Devices
- Model Pruning Enables Efficient Federated Learning on Edge Devices
- Split Learning for Health: Distributed Deep Learning without Sharing Raw Patient Data.
- Accelerating DNN Training in Wireless Federated Edge Learning System
- Towards Effective Device-Aware Federated Learning
- Federated Neuromorphic Learning of Spiking Neural Networks for Low-Power Edge Intelligence
- Asynchronous Online Federated Learning for Edge Devices
- Secure Federated Submodel Learning
- Lottery Hypothesis based Unsupervised Pre-training for Model Compression in Federated Learning
- SplitFed: When Federated Learning Meets Split Learning
- Distributed Learning on Heterogeneous Resource-Constrained Devices
-
System Design
- good
- BAFFLE : Blockchain based Aggregator Free Federated Learning
- Substra: a framework for privacy-preserving, traceable and collaborative Machine Learning
- Privacy is What We Care About: Experimental Investigation of Federated Learning on Edge Devices
- Quantifying the Performance of Federated Transfer Learning
- Decentralized knowledge acquisition for mobile internet applications - 17.
- Adaptive Gradient Sparsification for Efficient Federated Learning: An Online Learning Approach
- TiFL: A Tier-based Federated Learning System
- FMore: An Incentive Scheme of Multi-dimensional Auction for Federated Learning in MEC
- HierTrain: Fast Hierarchical Edge AI Learning with Hybrid Parallelism in Mobile-Edge-Cloud Computing
- Industrial Federated Learning -- Requirements and System Design
- Decentralised Learning from Independent Multi-Domain Labels for Person Re-Identification
- Heterogeneity-Aware Federated Learning
- FLeet: Online Federated Learning via Staleness Awareness and Performance Prediction
- Federated Learning and Differential Privacy: Software tools analysis, the Sherpa.ai FL framework and methodological guidelines for preserving data privacy
- FedML: A Research Library and Benchmark for Federated Machine Learning - AI/FedML](https://github.com/FedML-AI/FedML)]
- Flower: A Friendly Federated Learning Research Framework
- ELFISH: Resource-Aware Federated Learning on Heterogeneous Edge Devices
- Baseline
- HierTrain: Fast Hierarchical Edge AI Learning with Hybrid Parallelism in Mobile-Edge-Cloud Computing
- Baseline
- A generic framework for privacy preserving deep learning
- good
- BAFFLE : Blockchain based Aggregator Free Federated Learning
- Substra: a framework for privacy-preserving, traceable and collaborative Machine Learning
- Privacy is What We Care About: Experimental Investigation of Federated Learning on Edge Devices
- Quantifying the Performance of Federated Transfer Learning
- Adaptive Gradient Sparsification for Efficient Federated Learning: An Online Learning Approach
- TiFL: A Tier-based Federated Learning System
- FMore: An Incentive Scheme of Multi-dimensional Auction for Federated Learning in MEC
- Industrial Federated Learning -- Requirements and System Design
- Decentralised Learning from Independent Multi-Domain Labels for Person Re-Identification
- Heterogeneity-Aware Federated Learning
- FLeet: Online Federated Learning via Staleness Awareness and Performance Prediction
- Federated Learning and Differential Privacy: Software tools analysis, the Sherpa.ai FL framework and methodological guidelines for preserving data privacy
- FedML: A Research Library and Benchmark for Federated Machine Learning - AI/FedML](https://github.com/FedML-AI/FedML)]
- Flower: A Friendly Federated Learning Research Framework
- ELFISH: Resource-Aware Federated Learning on Heterogeneous Edge Devices
-
Speech Recognition
-
Smart City && Other Applications
- DIoT: A federated self-learning anomaly detection system for IoT - 767.
- Federated Multi-task Hierarchical Attention Model for Sensor Analytics
- Self-supervised audio representation learning for mobile devices
- Pmf: A privacy-preserving human mobility prediction framework via federated learning - 21.
- Exploiting Unlabeled Data in Smart Cities using Federated Learning
- Combining Federated and Active Learning for Communication-efficient Distributed Failure Prediction in Aeronautics
- Cloud-based Federated Boosting for Mobile Crowdsensing
- Cloud-based Federated Boosting for Mobile Crowdsensing
- Combining Federated and Active Learning for Communication-efficient Distributed Failure Prediction in Aeronautics
- Federated Multi-task Hierarchical Attention Model for Sensor Analytics
- Exploiting Unlabeled Data in Smart Cities using Federated Learning
-
Company
-
联邦学习工具基础能力测评
-
2022
- Adap
- Snips - buys-snips-ai-voice-assistant-privacy)
- Privacy.ai
- OpenMined
- Arkhn
- Scaleout
- MELLODDY
- DataFleets
- Owkin
- XAIN - fl): Automated Invoicing
- S20
- nvidia clare
- huawei NAIE
- 数犊科技
- 同态科技-迷雾计算
- TalkingData
- 融数联智
- 算数力科技-CompuTa
- 摩联科技
- ARPA-ARPA隐私计算协议
- 趣链科技-BitXMesh可信数据网络
- Adap
-
多方安全计算工具基础能力评测
-
可信执行环境计算平台基础能力评测
-
-
Blogs && Tutorials
-
2022
- Flower
- Online Comic from Google AI on Federated Learning
- PPT
- Under The Hood of The Pixel 2: How AI Is Supercharging Hardware
- An Introduction to Federated Learning
- Federated learning: Distributed machine learning with data locality and privacy
- Federated Learning: The Future of Distributed Machine Learning
- Federated Learning for Wake Word Detection
- An Open Framework for Secure and Privated AI
- A Brief Introduction to Differential Privacy
- An Overview of Federated Learning
- PySyft
- tensorflow TFF
- 杨强：联邦学习
- 联邦学习的研究及应用
- 杨强：GDPR对AI的挑战和基于联邦迁移学习的对策
- 联邦学习的研究与应用
- Federated Learning and Transfer Learning for Privacy, Security and Confidentiality - 19)
- GDPR, Data Shortage and AI - 19)
- GDPR, Data Shortage and AI - 19 Invited Talk)
- video - Qiang Yang, AAAI 2019 Invited Talk
- 谷歌发布全球首个产品级移动端分布式机器学习系统，数千万手机同步训练
- clara-federated-learning
- What is Federated Learning - Nvidia 2019
- nvidia-uses-federated-learning-to-create-medical-imaging-ai
- federated-learning-technique-predicts-hospital-stay-and-patient-mortality
- pubmed
- google-mayo-clinic-partnership-patient-data
- webank-clustar
- Private AI-Federated Learning with PySyft and PyTorch
- Federated Learning in 10 lines of PyTorch and PySyft
- A beginners Guided to Federated Learning - device AI, blockchain, and edge computing/IoT.
- video
- video
- video
- video - Google, 2018
- video
- An Overview of Federated Learning
- Private AI-Federated Learning with PySyft and PyTorch
- An Overview of Federated Learning
- Private AI-Federated Learning with PySyft and PyTorch
- An Overview of Federated Learning
- Private AI-Federated Learning with PySyft and PyTorch
- An Overview of Federated Learning
- Private AI-Federated Learning with PySyft and PyTorch
- An Overview of Federated Learning
- Private AI-Federated Learning with PySyft and PyTorch
- An Overview of Federated Learning
- Private AI-Federated Learning with PySyft and PyTorch
- An Overview of Federated Learning
- Private AI-Federated Learning with PySyft and PyTorch
- An Overview of Federated Learning
- Private AI-Federated Learning with PySyft and PyTorch
- Flower
- An Overview of Federated Learning
- Private AI-Federated Learning with PySyft and PyTorch
- An Overview of Federated Learning
- Private AI-Federated Learning with PySyft and PyTorch
- An Overview of Federated Learning
- Private AI-Federated Learning with PySyft and PyTorch
- An Overview of Federated Learning
- Private AI-Federated Learning with PySyft and PyTorch
- An Overview of Federated Learning
- nvidia-uses-federated-learning-to-create-medical-imaging-ai
- federated-learning-technique-predicts-hospital-stay-and-patient-mortality
- Private AI-Federated Learning with PySyft and PyTorch
- Private AI-Federated Learning with PySyft and PyTorch
- An Overview of Federated Learning
- An Overview of Federated Learning
- Private AI-Federated Learning with PySyft and PyTorch
- An Overview of Federated Learning
- Private AI-Federated Learning with PySyft and PyTorch
-
-
Framework
-
2022
-
-
Projects
-
Datasets && Benchmark
-
2022
- Federated iNaturalist/Landmarks
- Leaf: A benchmark for federated settings - pytorch](https://github.com/SMILELab-FL/FedLab-benchmarks/tree/master/fedlab_benchmarks/leaf)
- Edge AIBench: Towards Comprehensive End-to-end Edge Computing Benchmarking
- Real-World Image Datasets for Federated Learning
- Revocable Federated Learning: A Benchmark of Federated Forest
- PrivacyFL: A simulator for privacy-preserving and secure federated learning
- Evaluation Framework For Large-scale Federated Learning
- The OARF Benchmark Suite: Characterization and Implications for Federated Learning Systems - Computing/OARF)
- Performance Optimization for Federated Person Re-identification via Benchmark Analysis - ntu/FedReID](https://github.com/cap-ntu/FedReID)]
- Federated Learning on Non-IID Data Silos: An Experimental Study - Computing/NIID-Bench)
- FedGraphNN: A Federated Learning System and Benchmark for Graph Neural Networks - AI/FedGraphNN)
- DIDL
- Functional Federated Learning in Erlang (ffl-erl)
- Performance Optimization for Federated Person Re-identification via Benchmark Analysis - ntu/FedReID](https://github.com/cap-ntu/FedReID)]
- Functional Federated Learning in Erlang (ffl-erl)
- Revocable Federated Learning: A Benchmark of Federated Forest
- PrivacyFL: A simulator for privacy-preserving and secure federated learning
- Evaluation Framework For Large-scale Federated Learning
- The OARF Benchmark Suite: Characterization and Implications for Federated Learning Systems - Computing/OARF)
- DIDL
- Real-World Image Datasets for Federated Learning
-
-
Scholars
-
Conferences and Workshops
-
2022
- FL-ICML 2020 - Organized by IBM Watson Research.
- FL-IBM 2020 - Organized by IBM Watson Research and Webank.
- FL-NeurIPS 2019 - Organized by Google, Webank, NTU, CMU.
- FL-IJCAI 2019 - Organized by Webank.
- Google Federated Learning workshop - Organized by Google.
-
-
参考来源
Programming Languages
Categories
Uncategorized
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