Optimal Thresholding Linear Bandit
<|reference_start|>Optimal Thresholding Linear Bandit: We study a novel pure exploration problem: the $\epsilon$-Thresholding Bandit Problem (TBP) with fixed confidence in stochastic linear bandits. We prove a lower bound for the sample complexity and extend an algorithm designed for Best Arm Identification in the linear case to TBP that is asymptotically optimal.<|reference_end|>
@article{rivera2024optimal,
    title={Optimal Thresholding Linear Bandit},
    author={Eduardo Ochoa Rivera and Ambuj Tewari},
    journal={arXiv preprint arXiv:2402.09467},
    year={2024},
    archivePrefix={arXiv},
    eprint={2402.09467},
    primaryClass={stat.ML cs.LG}
}