管理科学系学术讲座

时    间：2023年5月30日（周二） 10:00-11:30

地    点：腾讯会议，会议ID: 983643345，密码: 230530

主    题：Valid Inference for A/B Tests with Treatment Parameter Optimization

主讲人：Zeyu Zheng  加州大学伯克利分校副教授

主持人：洪流 复旦大学管理学院教授

摘    要：

Constructing asymptotically valid confidence intervals through a valid central limit theorem (CLT) is crucial for controlled experiments or the so-called A/B tests. In particular, establishing a valid CLT can help statistically assert whether a treatment plan (B) is significantly better than a control plan (A), and can help construct confidence intervals. That said, in some emerging applications from online platforms, the treatment plan is not a single plan, but instead encompasses an infinite continuum of plans indexed by a continuous treatment parameter. As such, the experimenter has two tasks: (1) provide valid statistical inference, and (2) efficiently find the optimal choice of value for the treatment parameter to use for the treatment plan. The need to jointly deliver the two tasks creates theoretical challenges for algorithm design and existence of valid CLT. In this presentation, we discuss these challenges and propose solutions. We also discuss the connection of this research question to simulation optimization. 

主讲人简介：

Zeyu Zheng is an Assistant Professor from the Department of Industrial Engineering and Operations Research, at the University of California Berkeley. He received a PhD in Management Science and Engineering from Stanford University in 2018, an MA in Economics from Stanford University in 2016, and a BS in Mathematics from Peking University in 2012. He has done research in stochastic simulation and non-stationary stochastic modelling.

管理科学系

2023-5-24