Adversarial Robustness through Bias Variance Decomposition: A New Perspective for Federated Learning.

Yao Zhou|Jun Wu|Haixun Wang|Jingrui He


Anthology ID:DBLP:conf/cikm/Zhou0WH22
Volume:Proceedings of the 31st ACM International Conference on Information & Knowledge Management, Atlanta, GA, USA, October 17-21, 2022
Year:2022
Venue:International Conference on Information and Knowledge Management (CIKM)
Publisher:ACM
Pages:2753-2762
URL:https://doi.org/10.1145/3511808.3557232
DOI:https://doi.org/10.1145/3511808.3557232
DBLP:conf/cikm/Zhou0WH22
BibTeX:
@inproceedings{zhou-2022-adversarial, author = {Yao Zhou and Jun Wu and Haixun Wang and Jingrui He}, editor = {Mohammad Al Hasan and Li Xiong}, title = {{Adversarial Robustness through Bias Variance Decomposition: A New Perspective for Federated Learning}}, booktitle = {{Proceedings of the 31st ACM International Conference on Information & Knowledge Management, Atlanta, GA, USA, October 17-21, 2022}}, pages = {2753--2762}, publisher = {ACM}, year = {2022}, url = {https://doi.org/10.1145/3511808.3557232}, doi = {https://doi.org/10.1145/3511808.3557232} }