Web: http://arxiv.org/abs/2202.13001

Sept. 19, 2022, 1:13 a.m. | MohammadJavad Azizi, Thang Duong, Yasin Abbasi-Yadkori, András György, Claire Vernade, Mohammad Ghavamzadeh

stat.ML updates on arXiv.org arxiv.org

We study a sequential decision problem where the learner faces a sequence of
$K$-armed stochastic bandit tasks. An adversary may design the tasks, but the
adversary is constrained to choose the optimal arm of each task in a smaller
(but unknown) subset of $M$ arms. The task boundaries might be known (the
bandit meta-learning setting), or unknown (the non-stationary bandit setting).
We design an algorithm based on a reduction to bandit submodular maximization
and show that, in the regime of …

arxiv meta meta-learning set small

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