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Statistical Inference in Reinforcement Learning

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)

Naveen Jindal School of Management (JSOM), 12.210
800 W. Campbell Road, Richardson, Texas 75080-3021

Natural Sciences & Mathematics
Yunan Wu

UTD strives to create inclusive and accessible events in accordance with the Americans with Disabilities Act (ADA). If you require an accommodation to fully participate in this event, please contact the event coordinator (listed above) at least 10 business days prior to the event. If you have any additional questions, please email and the AccessAbility Resource Center at

  • Keshav Santhanam

1 person is interested in this event

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