seminars:datasci:110822
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| + | * Date: Tuesday, November 8, 2022 | ||
| + | * Time: 12:00pm -- 1:00pm | ||
| + | * Room: Via Zoom | ||
| + | * Speaker: Dr. Rui Song (senior principal scientist at Amazon; Professor at North Carolina State University) | ||
| + | * Title: On statistical inference for sequential decision making. | ||
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| + | Reinforcement learning is a general technique that allows an agent to | ||
| + | learn an optimal policy and interact with an environment in sequential | ||
| + | decision making problems. The goodness of a policy is measured by its | ||
| + | value function starting from some initial state. This talk includes a | ||
| + | few topics about constructing statistical inference for a policy' | ||
| + | value in infinite horizon settings where the number of decision points | ||
| + | diverges to infinity. Applications in real world examples will also be | ||
| + | discussed. | ||
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| + | Biography of the speaker: Dr. Song is currently a senior principal scientist at Amazon. She got | ||
| + | her PhD in Statistics from University of Wisconsin in 2006 and has | ||
| + | been a faculty member at North Carolina State University since 2012. | ||
| + | Her recent research focuses on adapting statistical advances to make | ||
| + | optimal treatment decisions for an individual patient, based on all | ||
| + | information available for that patient. She develops efficient and | ||
| + | powerful statistical approaches to use personalized, | ||
| + | information of patients in modeling, estimation, inference, selection | ||
| + | of important prognostic factors and evaluating treatment responses for | ||
| + | personalized treatment discoveries. Her research has been supported as | ||
| + | principal investigator by National Science Foundation (NSF) including | ||
| + | the NSF Faculty Early Career Development (CAREER) Award. She has | ||
| + | served as an associate editor for several statistical journals. She is | ||
| + | an elected Fellow of the American Statistical Association and | ||
| + | Institute of Mathematical Statistics. | ||
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