awesome-vertical-federated-learning
A curated list of advancements in Vertical Federated Learning, frameworks and libraries.
https://github.com/ngc436/awesome-vertical-federated-learning
Last synced: 1 day ago
JSON representation
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Publications in Top-tier Conferences (or influential)
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VFL benchmarks (benchmarks with VFL tasks)
- Stalactite: Toolbox for Fast Prototyping of Vertical Federated Learning Systems - ai-lab/Stalactite) | --- |
- The OARF Benchmark Suite: Characterization and Implications for Federated Learning Systems - Computing/OARF?tab=readme-ov-file#the-oarf-benchmark-suite-characterization-and-implications-for-federated-learning-systems) | --- |
- Fedml: A research library and benchmark for federated machine learning - AI/FedML/) | --- |
- VertiBench: Advancing Feature Distribution Diversity in Vertical Federated Learning Benchmarks - Computing/VertiBench) [Website](http://vertibench.xtra.science) | [GAL](https://openreview.net/forum?id=MT1GId7fJiP¬eId=Dl2kGghM_tQ), [C-VFL](https://arxiv.org/abs/2206.08330), SecureBoost, Pivot, [FedTree](https://github.com/Xtra-Computing/FedTree), [FedOnce](https://github.com/JerryLife/FedOnce) |
- VFLAIR: A Research Library and Benchmark for Vertical Federated Learning - thu/vflair) | --- |
- FedAds: A Benchmark for Privacy-Preserving CVR Estimation with Vertical Federated Learning - Federated-Learning-Solution/tree/FedAds) | --- |
- FedAds: A Benchmark for Privacy-Preserving CVR Estimation with Vertical Federated Learning - Federated-Learning-Solution/tree/FedAds) | --- |
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VFL algorithms
- Vertical federated machine learning without peeking into your data - | 2022 | SIGMOD |
- Privacy preserving vertical federated learning for tree-based models
- Vf2boost: Very fast vertical federated gradient boosting for cross-enterprise learning - | 2021 | SIGMOD |
- OpBoost: A Vertical Federated Tree Boosting Framework Based on Order-Preserving Desensitization
- Federated Transformer: Multi-Party Vertical Federated Learning on Practical Fuzzily Linked Data - Computing/FeT) | 2024 | Neurips |
- Practical vertical federated learning with unsupervised representation learning
- Secureboost: A lossless federated learning framework - | 2021 | IEEE Intelligent Systems |
- Fedtree: A federated learning system for trees - Computing/FedTree) | 2023 | MLSyS |
- Assisted learning: A framework for multiorganization learning - | 2020 | Neurips |
- Gal: Gradient assisted learning for decentralized multi-organization collaborations - Gradient-Assisted-Learning-for-Decentralized-Multi-Organization-Collaborations) | 2022 | Neurips |
- Split learning for health: Distributed deep learning without sharing raw patient data - | 2018 | Arxiv |
- Compressed-VFL: Communication-efficient learning with vertically partitioned data - VFL) | 2022 | ICML |
- Federated forest - | 2020 | IEEE Transactions on Big Data |
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VFL privacy
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VFL metrics / feature importance estimation
- Fair and Efficient Contribution Valuation for Vertical Federated Learning - vertical federated Shapley value (VerFedSV) |
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Surveys on VFL
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VFL Datasets (or datasets that are used in benchmarks)
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VFL metrics / feature importance estimation
- Link - |
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- Link - channel 158x158 | 4 |
- Link
- Link - | 581,012 | 54 | 7 |
- Link - | 463,715 | 90 | - |
- Link - | 72,309 | 20,958 | 2 |
- Link - | 60,000 | 5,000 | 2 |
- Link - | 400,000 | 2,000 | 2 |
- Link - | 15,000 | 16 | 26 |
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- Link
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- link - | 45,006,432 | 23 | 2 |
- Link - | 325,834 | 174 | 7 |
- Link - | 60,000 | 1,024 | 10 |
- Link - | 60,000 | 1,024 | 100 |
- Link - | 569 | 32 | 2 |
- Link - | 768 | 9 | 2 |
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Frameworks and Libraries with VFL support
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