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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,…