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CRiSM seminar 24/11/21, 2-3 pm

Speaker: Chengchun Shi
Title: Statistical inference in reinforcement learning
Abstract: Reinforcement learning is concerned with how intelligence agents take actions in a given environment to maximize the cumulative reward they receive. It 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 today's talk, I will discuss some of my recent work on developing statistical inferential tools for reinforcement learning.