Dying Experts: Efficient Algorithms with Optimal Regret Bounds

NeurIPS 2019 Hamid ShayestehmaneshSajjad AzamiNishant A. Mehta

We study a variant of decision-theoretic online learning in which the set of experts that are available to Learner can shrink over time. This is a restricted version of the well-studied sleeping experts problem, itself a generalization of the fundamental game of prediction with expert advice... (read more)

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