An Efficient Algorithm for Learning with Semi-bandit Feedback

DOI10.1007/978-3-642-40935-6_17zbMath1406.68099arXiv1305.2732OpenAlexW1561097743MaRDI QIDQ2859220

Gábor Bartók, Gergely Neu

Publication date: 6 November 2013

Published in: Lecture Notes in Computer Science (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1305.2732

zbMATH Keywords

combinatorial optimizationonline learningbandit problemsfollow-the-perturbed-leader

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Combinatorial optimization (90C27) General considerations in statistical decision theory (62C05)

Related Items (4)

Unnamed Item ⋮ An improved upper bound on the expected regret of UCB-type policies for a matching-selection bandit problem ⋮ Unnamed Item ⋮ Online Learning over a Finite Action Set with Limited Switching

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