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stat.ML2025
Catoni Contextual Bandits are Robust to Heavy-tailed Rewards
Chenlu Ye, Yujia Jin, Alekh Agarwal +1
Typical contextual bandit algorithms assume that the rewards at each round lie in some fixed range , and their regret scales polynomially with this reward range . Howeve…
stat.ML2024
Towards Robust Model-Based Reinforcement Learning Against Adversarial Corruption
Chenlu Ye, Jiafan He, Quanquan Gu +1
This study tackles the challenges of adversarial corruption in model-based reinforcement learning (RL), where the transition dynamics can be corrupted by an adversary. Existing stu…