26 citations · 54 across the 10 of their papers we have counts for
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cs.LG2021★ 2 cited
A Minimax Learning Approach to Off-Policy Evaluation in Confounded Partially Observable Markov Decision Processes
Chengchun Shi, Masatoshi Uehara, Jiawei Huang +1
We consider off-policy evaluation (OPE) in Partially Observable Markov Decision Processes (POMDPs), where the evaluation policy depends only on observable variables and the behavio…
cs.LG2021★ 1 cited
On the Convergence Rate of Off-Policy Policy Optimization Methods with Density-Ratio Correction
Jiawei Huang, Nan Jiang
In this paper, we study the convergence properties of off-policy policy improvement algorithms with state-action density ratio correction under function approximation setting, wher…