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cs.LG2023
Sample Complexity of Preference-Based Nonparametric Off-Policy Evaluation with Deep Networks
Zihao Li, Xiang Ji, Minshuo Chen +1
A recently popular approach to solving reinforcement learning is with data from human preferences. In fact, human preference data are now used with classic reinforcement learning a…
cs.LG2023★ 1 cited
Sample Complexity of Neural Policy Mirror Descent for Policy Optimization on Low-Dimensional Manifolds
Zhenghao Xu, Xiang Ji, Minshuo Chen +2
Policy gradient methods equipped with deep neural networks have achieved great success in solving high-dimensional reinforcement learning (RL) problems. However, current analyses c…
cs.LG2023
Provable Benefits of Policy Learning from Human Preferences in Contextual Bandit Problems
Xiang Ji, Huazheng Wang, Minshuo Chen +2
For a real-world decision-making problem, the reward function often needs to be engineered or learned. A popular approach is to utilize human feedback to learn a reward function fo…