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Speaker: Mr. Chuanhao Li From: University of Virginia Abstract Interactive decision making (e.g., bandit and reinforcement learning) is a promising paradigm for developing intelligent systems capable of efficiently exploring unknown environments. It has achieved remarkable success in recommender systems, clinical decision systems, robotics and cyber-physical systems, game playing, etc. Most prior efforts in the theoretical foundations of this paradigm consider …
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