Non-IID always Bad? Semi-Supervised Heterogeneous Federated Learning with Local Knowledge Enhancement.

Chao Zhang|Fangzhao Wu|Jingwei Yi|Derong Xu|Yang Yu|Jindong Wang|Yidong Wang|Tong Xu|Xing Xie|Enhong Chen


Anthology ID:DBLP:conf/cikm/ZhangWYXYWWXXC23
Volume:Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, CIKM 2023, Birmingham, United Kingdom, October 21-25, 2023
Year:2023
Venue:International Conference on Information and Knowledge Management (CIKM)
Publisher:ACM
Pages:3257-3267
URL:https://doi.org/10.1145/3583780.3614991
DOI:https://doi.org/10.1145/3583780.3614991
DBLP:conf/cikm/ZhangWYXYWWXXC23
BibTeX:
@inproceedings{zhang-2023-noniid, author = {Chao Zhang and Fangzhao Wu and Jingwei Yi and Derong Xu and Yang Yu and Jindong Wang and Yidong Wang and Tong Xu and Xing Xie and Enhong Chen}, editor = {Ingo Frommholz and Frank Hopfgartner and Mark Lee and Michael P. Oakes and Mounia Lalmas-Roelleke and Min Zhang and Rodrygo L. T. Santos}, title = {{Non-IID always Bad? Semi-Supervised Heterogeneous Federated Learning with Local Knowledge Enhancement}}, booktitle = {{Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, CIKM 2023, Birmingham, United Kingdom, October 21-25, 2023}}, pages = {3257--3267}, publisher = {ACM}, year = {2023}, url = {https://doi.org/10.1145/3583780.3614991}, doi = {https://doi.org/10.1145/3583780.3614991} }