• Corpus ID: 233740346

# Impact of Representation Learning in Linear Bandits

@inproceedings{Yang2021ImpactOR,
title={Impact of Representation Learning in Linear Bandits},
author={Jiaqi Yang and Wei Hu and Jason D. Lee and Simon Shaolei Du},
booktitle={ICLR},
year={2021}
}
• Published in ICLR 13 October 2020
• Computer Science
We study how representation learning can improve the efficiency of bandit problems. We study the setting where we play $T$ linear bandits with dimension $d$ concurrently, and these $T$ bandit tasks share a common $k (\ll d)$ dimensional linear representation. For the finite-action setting, we present a new algorithm which achieves $\widetilde{O}(T\sqrt{kN} + \sqrt{dkNT})$ regret, where $N$ is the number of rounds we play for each bandit. When $T$ is sufficiently large, our algorithm…
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