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20222026
most citedDouble Pessimism is Provably Efficient for Distributionally Robust Offline Reinforcement Learning: Generic Algorithm and Robust Partial Coverage

2 citations · 4 across the 9 of their papers we have counts for

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3 papers · 1 filter

stat.ML2026

Robust Assortment Optimization from Observational Data

Miao Lu, Yuxuan Han, Han Zhong +2

Assortment optimization is a fundamental challenge in modern retail and recommendation systems, where the goal is to select a subset of products that maximizes expected revenue und…

stat.ML2025

Learning an Optimal Assortment Policy under Observational Data

Yuxuan Han, Han Zhong, Miao Lu +2

We study the fundamental problem of offline assortment optimization under the Multinomial Logit (MNL) model, where sellers must determine the optimal subset of the products to offe…

stat.ML2022★ 2 cited

Statistical Estimation of Confounded Linear MDPs: An Instrumental Variable Approach

Miao Lu, Wenhao Yang, Liangyu Zhang +1

In an Markov decision process (MDP), unobservable confounders may exist and have impacts on the data generating process, so that the classic off-policy evaluation (OPE) estimators…