Dying Experts: Efficient Algorithms with Optimal Regret Bounds

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. Simila...

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Veröffentlicht in:	arXiv.org 2019-10
Hauptverfasser:	Shayestehmanesh, Hamid, Azami, Sajjad, Mehta, Nishant A
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Decision theory Experts Lower bounds Machine learning Ranking Sleep Upper bounds
Online-Zugang:	Volltext
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