Dive into Federated Learning

Tutorials and paper lists for federated learning.

Wish this can help you dive into FL more easily.

关于联邦学习的教程和论文列表。希望能方便大家入门联邦学习。

[toc]

Tutorials 教程

• [NeurIPS 2020] Federated Learning Tutorial [Web] [Slides] [Video]
• 联邦学习入门教程参考

Survey 综述

• [ICLR-DPML 2021] FedGraphNN: A Federated Learning System and Benchmark for Graph Neural Networks [Paper] [Code]
• [arXiv 2021] Federated Graph Learning -- A Position Paper [Paper]
• [IEEE TKDE 2021] A Survey on Federated Learning Systems: Vision, Hype and Reality for Data Privacy and Protection [Paper]
• [arXiv 2021] A Survey of Fairness-Aware Federated Learning [Paper]
• [Foundations and Trends in Machine Learning 2021] Advances and Open Problems in Federated Learning [Paper] [Chinese Version] [FL FAQ]
• [arXiv 2020] Towards Utilizing Unlabeled Data in Federated Learning: A Survey and Prospective [Paper]
• [IEEE Signal Processing Magazine 2020] Federated Learning: Challenges, Methods, and Future Directions [Paper]
• [IEEE Communications Surveys & Tutorials 2020] Federated Learning in Mobile Edge Networks A Comprehensive Survey [Paper]
• [IEEE TIST 2019] Federated Machine Learning: Concept and Applications [Paper]

Frameworks 框架

• FedLab: Code, FedLab-benchmarks, Doc (zh-CN-Doc), Paper
• Flower: Code, Homepage, Doc, Paper
• FedML: Code, Doc, Paper
• FedLearn: Code, Paper
• PySyft: Code, Doc, Paper
• TensorFlow Federated (TFF): Code, Doc
• FEDn: Code, Paper
• FATE: Code, Homepage, Doc, Paper
• PaddleFL: Code, Doc
• Fedlearner: Code
• OpenFL: Code, Doc, Paper
• FedScale: Code, Paper
• FLSim: Code
• EasyFL: Code, Doc, Paper
• FederatedScope: Code, Homepage

Benchmarks 基准

• FedLab-benchmarks: Code
• [ACM TIST 2022] The OARF Benchmark Suite: Characterization and Implications for Federated Learning Systems [Code] [Paper]
• [IEEE ICDE 2022] Federated Learning on Non-IID Data Silos: An Experimental Study [Paper] [Official Code] [FedLab Tutorial]
• [ICLR-DPML 2021] FedGraphNN: A Federated Learning System and Benchmark for Graph Neural Networks [Paper] [Code]
• [arXiv 2018] LEAF: A Benchmark for Federated Settings [Homepage] [Official tensorflow] [Unofficial PyTorch] [Paper]

FL+Semi-supervised Learning 联邦半监督

• [ICLR 2021] Federated Semi-supervised Learning with Inter-Client Consistency & Disjoint Learning [Paper] [Code]
• [arXiv 2021] SemiFL: Communication Efficient Semi-Supervised Federated Learning with Unlabeled Clients [Paper]
• [IEEE BigData 2021] Improving Semi-supervised Federated Learning by Reducing the Gradient Diversity of Models [Paper]
• [arXiv 2020] Benchmarking Semi-supervised Federated Learning [Paper]] [Code]

FL+HPC 联邦高性能计算

• [arXiv 2022] Sky Computing: Accelerating Geo-distributed Computing in Federated Learning [Paper] [Code]
• [ACM HPDC 2020] TiFL: A Tier-based Federated Learning System [Paper] [Video]

Blogs 博客

• 无知者：联邦学习系统前沿
• 无知者：联邦学习开源框架FedLab相关
• lokinko:联邦学习论文分享
• AgentDS：划水运动员假装在学术

Awesome List

• lokinko/Federated-Learning
• chaoyanghe/Awesome-Federated-Learning
• weimingwill/awesome-federated-learning
• tushar-semwal/awesome-federated-computing
• ZeroWangZY/federated-learning
• innovation-cat/Awesome-Federated-Machine-Learning
• huweibo/Awesome-Federated-Learning-on-Graph-and-GNN-papers