@inproceedings{Cutkosky2022LeveragingIH,
author={Ashok Cutkosky and Christoph Dann and Abhimanyu Das and Qiuyi Zhang},
booktitle={ALT},
year={2022}
}
• Published in ALT 8 March 2022
• Computer Science
We study the setting of optimizing with bandit feedback with additional prior knowledge provided to the learner in the form of an initial hint of the optimal action. We present a novel algorithm for stochastic linear bandits that uses this hint to improve its regret to Õ( √ T ) when the hint is accurate, while maintaining a minimax-optimal Õ(d √ T ) regret independent of the quality of the hint. Furthermore, we provide a Pareto frontier of tight tradeoffs between best-case and worstcase regret…

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