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)

PDF Abstract


No code implementations yet. Submit your code now


Results from the Paper

  Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers.