A Robust Clustered Federated Learning Approach for Non-IID Data with Quantity Skew.
Michael Ben Ali|Imen Megdiche|André Péninou|Olivier Teste
| Anthology ID: | DBLP:conf/cikm/AliMPT25 |
|---|---|
| Volume: | Proceedings of the 34th ACM International Conference on Information and Knowledge Management, CIKM 2025, Seoul, Republic of Korea, November 10-14, 2025 |
| Year: | 2025 |
| Venue: | International Conference on Information and Knowledge Management (CIKM) |
| Publisher: | ACM |
| Pages: | 149-158 |
| URL: | https://doi.org/10.1145/3746252.3761216 |
| DOI: | https://doi.org/10.1145/3746252.3761216 |
| DBLP: | conf/cikm/AliMPT25 |
| BibTeX: |
@inproceedings{ali-2025-robust,
author = {Michael Ben Ali and
Imen Megdiche and
Andr\'{e} P\'{e}ninou and
Olivier Teste},
editor = {Meeyoung Cha and
Carl Yang and
Senjuti Basu Roy and
Chanyoung Park and
Zhenhui Jessie Li and
Noseong Park and
Carl Yang and
Senjuti Basu Roy and
Zhenhui Jessie Li and
Jaap Kamps and
Kijung Shin and
Bryan Hooi and
Lifang He},
title = {{A Robust Clustered Federated Learning Approach for Non-IID Data with Quantity Skew}},
booktitle = {{Proceedings of the 34th ACM International Conference on Information and Knowledge Management, CIKM 2025, Seoul, Republic of Korea, November 10-14, 2025}},
pages = {149--158},
publisher = {ACM},
year = {2025},
url = {https://doi.org/10.1145/3746252.3761216},
doi = {https://doi.org/10.1145/3746252.3761216}
}