A curated list of research in federated learning. Link to the code if available is also present. You are very welcome to pull request by using our template.
Last update: 04 Dec, 2020
- Statistical Heterogeneity
- Communication Efficiency
- System: federated learning system design, frameworks, edge AI, etc.
- Trustworthiness: privacy, security, fairness
- Decentralzied FL
- Applications
- Vertical FL
- FL + {X}: FL + reinforcement learning, FL + transfer learning, etc.
- Communication-Efficient Learning of Deep Networks from Decentralized Data [Paper] [Github] [Google] [Must Read]
- Federated learning paper by conferences: NIPS, ICML, ICLR, etc.
- Federated Learning Comic [Google Blog]
- Federated Learning: Collaborative Machine Learning without Centralized Training Data [Google Blog]
- Federated Machine Learning: Concept and Applications [Paper]
- Federated Learning: Challenges, Methods, and Future Directions [Paper]
- Advances and Open Problems in Federated Learning [Paper]
- Federated Learning White Paper V1.0 [Paper]
- Federated Learning Systems: Vision, Hype and Reality for Data Privacy and Protection [Paper]
- Federated Learning in Mobile Edge Networks: A Comprehensive Survey [Paper]
- Federated Learning for Wireless Communications: Motivation, Opportunities and Challenges [Paper]
- A Review of Applications in Federated Learning [Paper]
- LEAF: A Benchmark for Federated Settings [Paper] [Github] [Recommend]
- The OARF Benchmark Suite: Characterization and Implications for Federated Learning Systems [Paper]
- Performance Optimization for Federated Person Re-identification via Benchmark Analysis [Paper] [ACMMM20] [Github]
- A Performance Evaluation of Federated Learning Algorithms [Paper]
- Edge AIBench: Towards Comprehensive End-to-end Edge Computing Benchmarking [Paper]
- GDPR, Data Shotrage and AI (AAAI-19) [Video]
- Federated Learning: Machine Learning on Decentralized Data (Google I/O'19) [Youtube]
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