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} }