统计与数据科学系系列学术报告之四百六十四期
时 间： 2025年4月8日（周二）16:00-17:00
主持人：复旦大学 管理学院 统计与数据科学系 戴国榕 博士
地 点：史带楼302室
报 告 人：张宇谦 助理教授
中国人民大学
题 目：Balancing utility and cost in dynamic treatment regimes
摘 要：Dynamic treatment regimes (DTRs) are personalized, adaptive strategies designed to guide the sequential allocation of treatments based on individual characteristics over time. Before each treatment assignment, covariate information is collected to refine treatment decisions and enhance their effectiveness. The more information we gather, the more precise our decisions can be. However, this also leads to higher costs during the data collection phase. In this work, we propose a balanced Q-learning method that strikes a balance between the utility of the DTRs and the costs associated with both treatment assignment and covariate assessment. The performance of the proposed method is demonstrated through extensive numerical studies.
个人简介：张宇谦，中国人民大学统计与大数据研究院助理教授，博士生导师。2016年本科毕业于武汉大学，2022年博士毕业于美国加州大学圣地亚哥分校。主要研究方向包括因果推断、半监督学习、高维统计、机器学习理论、缺失数据、精准医疗等。文章发表于Annals of Statistics、Biometrika、Information and Inference等期刊。主持国家自然科学基金青年基金项目一项，参与面上项目一项。曾获美国统计协会非参数统计组最佳学生论文奖。
统计与数据科学系
2025-3-19
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