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- Communication-Efficient Learning of Deep Networks from Decentralized Data, https://arxiv.org/abs/1602.05629
- Towards Federated Learning at Scale: System Design, https://arxiv.org/abs/1902.01046
- Adaptive Federated Optimization, https://arxiv.org/abs/2003.00295
- Advances and Open Problems in Federated Learning, https://arxiv.org/abs/1912.04977
- A Field Guide to Federated Optimization, https://arxiv.org/abs/2107.06917
- Federated Learning: Challenges, Methods, and Future Directions, https://arxiv.org/abs/1908.07873
Introduction to the Special Issue on the Federated Learning: Algorithms, Systems, and Applications: Part 1, https://dl.acm.org/toc/tist/2022/13/4, https://dl.acm.org/doi/full/10.1145/3514223,
- Federated Learning for Healthcare: Systematic Review and Architecture Proposal, https://dl.acm.org/doi/10.1145/3501813
- GTG-Shapley: Efficient and Accurate Participant Contribution Evaluation in Federated Learning, https://dl.acm.org/doi/10.1145/3501811
- Federated Learning One World Seminar, https://sites.google.com/view/one-world-seminar-series-flow/home, https://www.youtube.com/channel/UCpAXM9I-v76xEPtevcCuA5g
- WeBank/QiangYang, Recent Advances in Trustworthy Federated Learning, https://www.youtube.com/watch?v=tCBr_XQwPGY
- The Internet of Federated Things (IoFT): A Vision for the Future and In-depth Survey of Data-driven Approaches for Federated Learning, https://arxiv.org/abs/2111.05326, [YouTube] https://www.youtube.com/watch?v=RrubcIWCihk, [Site] https://ioft-data.engin.umich.edu/, https://sites.google.com/site/schungkorea/
[Google]
- Federated Learning Tutorial, https://sites.google.com/view/fl-tutorial/
- FL with Google, https://federated.withgoogle.com/
[한글]
- IITP, 인공지능 기술청사진 2030 2차년도 보고서, https://www.iitp.kr/kr/1/knowledge/openReference/view.it?ArticleIdx=5248&count=true
- “중앙집중식 ML 방식에서 로컬라이징” [특별기획 AI 2030] ⑲ 연합학습, https://www.aitimes.com/news/articleView.html?idxno=136724
- 연합학습 기술 동향 및 산업적 시사점 [기술정책 트렌드 2020-06], https://www.itfind.or.kr/publication/regular/periodical/read.do?selectedId=02-001-201223-000002&fbclid=IwAR2kkwI-9n3pwzROqvkLSjCW9XKT6fs5K62jv9Ery-0-aTxtGLEGryiUxrQ
- 동적인 디바이스 환경에서 적응적 연합학습 기술, https://itfind.or.kr/publication/regular/weeklytrend/pastList/read.do?selectedId=1237
- 동적인 디바이스 환경에서 적응적 연합학습기술 개발 (Adaptive Federated Learning in Dynamic Heterogeneous Environment), https://github.com/Kwangkee/FL/blob/main/AFL.md
- 엣지 컴퓨팅과 연합학습을 활용한 제조 공정의 AI 데이터 분석 모델의 제안, https://www.itfind.or.kr/publication/regular/weeklytrend/weekly/list.do?selectedId=1248
[한글 동영상 강의]
- 연합학습 기초, https://www.laidd.org/course/105
- 연합 학습 연구 동향, https://laidd.org/course/130
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