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routineStatistical & Classical MLBest-Arm Identification2608.19903

Where Does the Union Bound Go? Best-Arm Identification and Strong FWER Control

Rianne de Heide

stat.ME cs.LG stat.ML

Abstract

In fixed-confidence best-arm identification, proofs often use a union bound across the competing arms. From a multiple-testing point of view this can look puzzling: if the best arm is unique, only one hypothesis of the form ``arm $i$ is best'' can be true. Why then should there be a Bonferroni-type factor of $K-1$? The answer is that there are two natural ways to orient the hypotheses. In one orientation, best-arm identification is literally a strong familywise-error-rate (FWER) problem with $K-1$ true nulls. In the opposite orientation, exactly one null is true, but a pairwise implementation can falsely reject that one null through any of $K-1$ comparisons. Thus the multiplicity has not disappeared; it just pops up in different places. This note makes the equivalence explicit in the terminology of both communities.

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Classified with taxonomy v2 on Wed, 2 Sept 2026.

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