讲座题目：Statistical Infernece in Reinforcement Learning
讲座时间：2024.12.24（周二）15:00-16:30
讲座地点：新主楼A618
讲座嘉宾：史成春 副教授
讲座嘉宾 简介
Chengchun Shi is an Associate Professor at London School of Economics and Political Science. He is serving as the associate editors of JRSSB, JASA (TM), JASA (CS) and Journal of Nonparametric Statistics. His research focuses on developing statistical learning methods in reinforcement learning, with applications to healthcare, ridesharing, video-sharing and neuroimaging. He was the recipient of the Royal Statistical Society Research Prize in 2021 and IMS Tweedie Award in 2024.
讲座概要
Reinforcement learning (RL) is concerned with how intelligence agents take actions in a given environment to maximize the cumulative reward they receive. In healthcare, applying RL algorithms could assist patients in improving their health status. In ride-sharing platforms, applying RL algorithms could increase drivers' income and customer satisfaction. RL has been arguably one of the most vibrant research frontiers in machine learning over the last few years. Nevertheless, statistics as a field, as opposed to computer science, has only recently begun to engage with reinforcement learning both in depth and in breadth. In this talk, I will discuss some of my recent work on developing statistical inferential tools for reinforcement learning, with applications to mobile health and ride-sharing companies. The talk will cover several different papers published in highly-ranked statistical journals (JASA & JRSS-B) and top machine learning conferences (ICML & NeurIPS).
