Provably Robust Federated Reinforcement Learning.
Minghong Fang|Xilong Wang|Neil Zhenqiang Gong
| Anthology ID: | DBLP:conf/www/FangWG25 |
|---|---|
| Volume: | Proceedings of the ACM on Web Conference 2025, WWW 2025, Sydney, NSW, Australia, 28 April 2025- 2 May 2025 |
| Year: | 2025 |
| Venue: | The Web Conference (WWW) |
| Publisher: | ACM |
| Pages: | 896-909 |
| URL: | https://doi.org/10.1145/3696410.3714728 |
| DOI: | https://doi.org/10.1145/3696410.3714728 |
| DBLP: | conf/www/FangWG25 |
| BibTeX: |
@inproceedings{fang-2025-provably,
author = {Minghong Fang and
Xilong Wang and
Neil Zhenqiang Gong},
editor = {Guodong Long and
Michale Blumestein and
Yi Chang and
Liane Lewin-Eytan and
Zi Huang and
Elad Yom-Tov},
title = {{Provably Robust Federated Reinforcement Learning}},
booktitle = {{Proceedings of the ACM on Web Conference 2025, WWW 2025, Sydney, NSW, Australia, 28 April 2025- 2 May 2025}},
pages = {896--909},
publisher = {ACM},
year = {2025},
url = {https://doi.org/10.1145/3696410.3714728},
doi = {https://doi.org/10.1145/3696410.3714728}
}