AI Seminar Series 2021: Chenjun Xiao

The AI Seminar is a weekly meeting at the University of Alberta where researchers interested in artificial intelligence (AI) can share their research. Presenters include both local speakers from the University of Alberta and visitors from other institutions. Topics can be related in any way to artificial intelligence, from foundational theoretical work to innovative applications of AI techniques to new fields and problems.

On November 12, Chenjun Xiao, PhD student at the University of Alberta and researcher at Google Brain, presented “On the Optimality of Batch Policy Optimization Algorithms” at the AI Seminar.

Batch policy optimization is an area that has drawn significant interest in recent years. However, its theoretical foundations remain underdeveloped. Xiao’s presentation explores three results that shed light on the limits and possibilities of batch policy optimization in a finite-armed stochastic bandit setting.

Watch the full presentation below:

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