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Almost Optimal Variance-Constrained Best Arm Identification. (arXiv:2201.10142v1 [cs.LG])
Jan. 26, 2022, 2:11 a.m. | Yunlong Hou, Vincent Y. F. Tan, Zixin Zhong
cs.LG updates on arXiv.org arxiv.org
We design and analyze VA-LUCB, a parameter-free algorithm, for identifying
the best arm under the fixed-confidence setup and under a stringent constraint
that the variance of the chosen arm is strictly smaller than a given threshold.
An upper bound on VA-LUCB's sample complexity is shown to be characterized by a
fundamental variance-aware hardness quantity $H_{VA}$. By proving a lower
bound, we show that sample complexity of VA-LUCB is optimal up to a factor
logarithmic in $H_{VA}$. Extensive experiments corroborate the …
More from arxiv.org / cs.LG updates on arXiv.org
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