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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…
eess.SY2024
Privacy-Preserving Resilient Vector Consensus
Bing Liu, Chengcheng Zhao, Li Chai +2
This paper studies privacy-preserving resilient vector consensus in multi-agent systems against faulty agents, where normal agents can achieve consensus within the convex hull of t…