Estimating Optimal Infinite Horizon Dynamic Treatment Regimes via pT-Learning
时间：2022-10-10
阅读量：641次
- 演讲人： 周文卓（University of California Irvine）
- 时间：2022年10月21日 周五上午10：00
- 地点：腾讯会议 ID：230-614-982
- 主办单位：浙江大学数据科学研究中心
摘要: Recent advances in mobile health (mHealth) technology provide an effective way to monitor individuals' health statuses and deliver just-in-time personalized interventions. However, the practical use of mHealth technology raises unique challenges to existing methodologies on learning an optimal dynamic treatment regime. Many mHealth applications involve decision-making with large numbers of intervention options and under an infinite time horizon setting where the number of decision stages diverges to infinity. In addition, temporary medication shortages may cause optimal treatments to be unavailable, while it is unclear what alternatives can be used. To address these challenges, we propose a Proximal Temporal consistency Learning (pT-Learning) framework to estimate an optimal regime that is adaptively adjusted between deterministic and stochastic sparse policy models. The resulting minimax estimator avoids the double sampling issue in the existing algorithms. It can be further simplified and can easily incorporate off-policy data without mismatched distribution corrections. We study theoretical properties of the sparse policy and establish finite-sample bounds on the excess risk and performance error. The proposed method is implemented by our proximalDTR package and is evaluated through extensive simulation studies and the OhioT1DM mHealth dataset. This is a joint work with Prof. Ruoqing Zhu and Prof. Annie Qu.
个人简介: Wenzhuo Zhou is a postdoctoral fellow in Statistics at the University of California Irvine, where he works with Professors Annie Qu and Babak Shahbaba. Prior to that, He got the Ph.D. in Statistics from the University of Illinois Urbana Champaign in 2022, advised by Professor Ruoqing Zhu. His research mainly focuses on the reinforcement learning, dynamic treatment regimes, and natural language processing. His works have been published in some statistical journals, including Journal of the American Statistical Association, Biometrika, etc.
联系人：崔逸凡（cuiyf@zju.edu.cn）