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AI Seminar Series 2022: Bingshan Hu

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 January 21, Bingshan Hu – Amii Postdoctoral Fellow – presented "(Near)-optimal Regret Bound for Differentially Private Thompson Sampling" at the AI Seminar.

In her talk, Hu focuses on the exploration/exploitation dilemma faced in multi-armed bandit problems – how often the learning algorithm should seek to gain new information compared to accumulating reward. She discusses Thompson Sampling, a learning algorithm that offers competitive performance and a good balance of exploration and exploitation, and presents a Thomspon Sampling-based algorithm for private stochastic bandits.

Watch the full presentation below:


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Learn how Amii advances world-leading artificial intelligence and machine learning research: visit our Research page.

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