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awesome-split-learning
A curated repository for various papers in the domain of split learning.
https://github.com/aidecentralized/awesome-split-learning
Last synced: about 24 hours ago
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Split Training
- Split learning for health: Distributed deep learning without sharing raw patient data
- SplitFed: When Federated Learning Meets Split Learning
- Advances and Open Problems in Federated Learning
- Comparison of Privacy-Preserving Distributed Deep Learning Methods in Healthcare
- Advancements of federated learning towards privacy preservation: from federated learning to split learning
- SplitEasy: A Practical Approach for Training ML models on Mobile Devices in a split second
- FedSL: Federated Split Learning on Distributed Sequential Data in Recurrent Neural Networks
- Multiple Classification with Split Learning
- Distributed Heteromodal Split Learning for Vision Aided mmWave Received Power Prediction
- End-to-End Evaluation of Federated Learning and Split Learning for Internet of Things
- Can We Use Split Learning on 1D CNN Models for Privacy Preserving Training?
- Communication-Efficient Multimodal Split Learning for mmWave Received Power Prediction
- Split Learning for collaborative deep learning in healthcare
- ExpertMatcher: Automating ML Model Selection for Clients using Hidden Representations
- Detailed comparison of communication efficiency of split learning and federated learning
- No Peek: A Survey of private distributed deep learning
- SplitGNN: Splitting GNN for Node Classification with Heterogeneous Attention
- split learning vertically
- Speed up federated learning in heterogeneous environment: A dynamic tiering approach
- Communication-Efficient Training Workload Balancing for Decentralized Multi-Agent Learning
- PFSL: Personalized & Fair Split Learning with Data & Label Privacy for thin clients
- split learning vertically
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Split Inference
- Interpretable Complex-Valued Neural Networks for Privacy Protection
- Mitigating_Information_Leakage_in_Image_Representations_A_Maximum_Entropy_Approach
- NoPeek: Information leakage reduction to share activations in distributed deep learning
- PRIVATE SPLIT INFERENCE OF DEEP NETWORKS
- DISCO: Dynamic and Invariant Sensitive Channel Obfuscation for deep neural networks
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