2 papers
cs.LG2025
FedShard: Federated Unlearning with Efficiency Fairness and Performance Fairness
Siyuan Wen, Meng Zhang, Yang Yang +1
To protect clients' right to be forgotten in federated learning, federated unlearning aims to remove the data contribution of leaving clients from the global learned model. While c…
cs.LG2025
Soft Weighted Machine Unlearning
Xinbao Qiao, Ningning Ding, Yushi Cheng +1
Machine unlearning, as a post-hoc processing technique, has gained widespread adoption in addressing challenges like bias mitigation and robustness enhancement, colloquially, machi…