3 papers
stat.ML2026
Sparse Additive Off-Policy Evaluation for Reinforcement Learning with Potentially Limited Number of Trajectories
Tuoyi Zhao, Chengchun Shi, Zhengling Qi +1
We develop a new framework for flexible, nonlinear, and interpretable off-policy evaluation for infinite-horizon reinforcement learning. To handle large state spaces and support tr…
stat.ML2024
Private Optimal Inventory Policy Learning for Feature-based Newsvendor with Unknown Demand
Tuoyi Zhao, Wen-xin Zhou, Lan Wang
The data-driven newsvendor problem with features has recently emerged as a significant area of research, driven by the proliferation of data across various sectors such as retail,…
stat.ME2022
Transformation-Invariant Learning of Optimal Individualized Decision Rules with Time-to-Event Outcomes
Yu Zhou, Lan Wang, Rui Song +1
In many important applications of precision medicine, the outcome of interest is time to an event (e.g., death, relapse of disease) and the primary goal is to identify the optimal…