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cs.LG2025
An Information-Theoretic Analysis for Federated Learning under Concept Drift
Fu Peng, Meng Zhang, Ming Tang
Recent studies in federated learning (FL) commonly train models on static datasets. However, real-world data often arrives as streams with shifting distributions, causing performan…
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…