In this webportal, we keep track of books, workshops, conference special tracks, journal special issues, standardization effort and other notable events related to the field of Federated Learning (FL).

Research Programmes

• Trustworthy Federated Ubiquitous Learning (TrustFUL) Research Lab, Funded by: AISG, Hosted by: Nanyang Technological University (NTU), Singapore.
• Toward Trustable Model-centric Sharing for Collaborative Machine Learning, Funded by: AISG, Hosted by: National University of Singapore (NUS), Singapore.

Books

• 杨强、黄安埠、刘洋、陈天健 《联邦学习实战》 电子工业出版社, p. 340 (2021).
• Yang, Q., Fan, L. & Yu, H. (Eds.). (2020). Federated Learning: Privacy and Incentive. Springer International Publishing, Switzerland, p. 282. (Google Scholar)
• 杨强、刘洋、程勇、 康炎、陈天健、于涵 《联邦学习》 电子工业出版社, p. 208 (2020).
• Yang, Q., Liu, Y., Cheng, Y., Kang, Y., Chen, T. & Yu, H. (2020). Federated Learning. Synthesis Lectures on Artificial Intelligence and Machine Learning. Springer, Cham, p. 189.

Journal Special Issues

• Special Issue on Trustworthy Federated Learning, IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2023.
• Special Issue on Trustable, Verifiable, and Auditable Federated Learning, IEEE Transactions on Big Data (TBD), 2022.
• Special Issue on Federated Learning: Algorithms, Systems, and Applications, ACM Transactions on Intelligent Systems and Technology (TIST), 2021.
• Special Issue on Federated Machine Learning, IEEE Intelligent Systems (IS), 2019.

Conference Special Tracks

• Special Session on Trustworthy Federated Learning for Multimedia, ICME'23, Brisbane, QN, Australia, 2023.
• "Federated Learning" included as a new keyword in IJCAI'20, Yokohama, Japan, 2020.
• Special Track on Federated Machine Learning, IEEE BigData'19, Los Angeles, CA, USA, 2019.

Workshops

• AI Technology School, 2022, Singapore
• FL-NeurIPS'22, New Orleans, LA, USA
• MBZUAI Workshop on Collaborative Learning: From Theory to Practice, Abu Dhabi, UAE
• Canadian AI Federated Learning Workshop 2022, Toronto, ON, Canada
• FL-IJCAI'22, Vienna, Austria
• FL-AAAI-22, Vancouver, BC, Canada (Virtual)
• FL-NeurIPS'21 (Virtual)
• The Federated Learning Workshop, 2021, Paris, France (Hybrid)
• PDFL-EMNLP'21, Bilbao, Spain (Virtual)
• FTL-IJCAI'21, Montreal, QB, Canada (Virtual)
• DeepIPR-IJCAI'21, Montreal, QB, Canada (Virtual)
• FL-ICML'21 (Virtual)
• RSEML-AAAI-21 (Virtual)
• NeurIPS-SpicyFL'20, Vancouver, BC, Canada (Virtual)
• FL-IJCAI'20, Yokohama, Japan (Virtual)
• FL-ICML'20, Vienna, Austria (Virtual)
• FL-IBM'20, New York, NY, USA
• FL-NeurIPS'19, Vancouver, BC, Canada
• FL-IJCAI'19, Macau
• FL-Google'19, Seattle, WA, USA

Wikipedia

• Federated Learning

Benchmark Datasets

• Federated AI Dataset
• LEAF

Tutorials

• Federated Learning on MNIST using a CNN, AI6101, 2020 (Watch Demo Video)
• Federated Learning: User Privacy, Data Security and Confidentiality in Machine Learning, AAAI-19, Honolulu, HI, USA

Standardization Effort

• IEEE P3652.1 Federated Machine Learning Working Group

Comics

• Federated Learning - An Online Comic from Google AI

Youtube Channels

• Federated AI

Frameworks

• Federated AI Technology Enabler (FATE)
• Tensorflow Federated
• FedML: A Research Library and Benchmark for Federated Machine Learning
• IBM Federated Learning Framework
• Fedlearner^TM

Communities

• Federated AI Ecosystem