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cs.LG2025
ImprovDML: Improved Trade-off in Private Byzantine-Resilient Distributed Machine Learning
Bing Liu, Chengcheng Zhao, Li Chai +2
Jointly addressing Byzantine attacks and privacy leakage in distributed machine learning (DML) has become an important issue. A common strategy involves integrating Byzantine-resil…
cs.LG2024
Near-Optimal Reinforcement Learning with Shuffle Differential Privacy
Shaojie Bai, Mohammad Sadegh Talebi, Chengcheng Zhao +2
Reinforcement learning (RL) is a powerful tool for sequential decision-making, but its application is often hindered by privacy concerns arising from its interaction data. This cha…