23 citations · 87 across the 27 of their papers we have counts for
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cs.LG2020★ 23 cited
Near-Optimal Provable Uniform Convergence in Offline Policy Evaluation for Reinforcement Learning
Ming Yin, Yu Bai, Yu-Xiang Wang
The problem of Offline Policy Evaluation (OPE) in Reinforcement Learning (RL) is a critical step towards applying RL in real-life applications. Existing work on OPE mostly focus on…
cs.LG2020★ 8 cited
Asymptotically Efficient Off-Policy Evaluation for Tabular Reinforcement Learning
Ming Yin, Yu-Xiang Wang
We consider the problem of off-policy evaluation for reinforcement learning, where the goal is to estimate the expected reward of a target policy using offline data collected b…