AdaLinUCB: Opportunistic Learning for Contextual Bandits

20 Feb 2019Xueying GuoXiaoxiao WangXin Liu

In this paper, we propose and study opportunistic contextual bandits - a special case of contextual bandits where the exploration cost varies under different environmental conditions, such as network load or return variation in recommendations. When the exploration cost is low, so is the actual regret of pulling a sub-optimal arm (e.g., trying a suboptimal recommendation)... (read more)

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