3 papers
cs.LG2024
Distributionally Robust Policy Learning under Concept Drifts
Jingyuan Wang, Zhimei Ren, Ruohan Zhan +1
Distributionally robust policy learning aims to find a policy that performs well under the worst-case distributional shift, and yet most existing methods for robust policy learning…
cs.LG2024
Adaptively Learning to Select-Rank in Online Platforms
Jingyuan Wang, Perry Dong, Ying Jin +2
Ranking algorithms are fundamental to various online platforms across e-commerce sites to content streaming services. Our research addresses the challenge of adaptively ranking ite…
stat.ML2019
Confidence Intervals for Policy Evaluation in Adaptive Experiments
Vitor Hadad, David A. Hirshberg, Ruohan Zhan +2
Adaptive experiment designs can dramatically improve statistical efficiency in randomized trials, but they also complicate statistical inference. For example, it is now well known…