时 间：2022年10月19日 15:30-17:00
地 点：腾讯会议ID：811-916-088
报告人：史成春 助理教授
主持人：石芸 副研究员
摘 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 today's talk, I will discuss some of my recent work on developing statistical inferential tools for reinforcement learning, with applications to mobile health and ridesharing companies. The talk will cover several different papers published in highly-ranked statistical journals (JASA & JRSSB) and top machine learning conferences (ICML)
报告人简介：
史成春是伦敦政治经济学院统计系的助理教授。他有近20篇第一作者同行评审的文章被顶级统计期刊AOS，JRSSB，JASA和JMLR接受。他还在顶级机器学习会议ICML 和 NeurIPS上发表了论文。他目前担任 JRSSB 和 Journal of Nonparametric Statistics 的副主编。他的研究主要是在强化学习中开发统计方法。他是 2021年皇家统计学会研究奖的获得者。他还获得三次 IMS Travel Award。