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papersSEP 10 04:00 UTC

Researchers prove gap-entropy conjecture for fixed-confidence best-arm identification

A new arXiv paper in machine learning theory settles the gap-entropy conjecture, an open problem in best-arm identification for multi-armed bandits. The proof covers the fixed-confidence setting with independent unit-variance Gaussian arms, means bounded in [0,1], and a single optimal arm. The result confirms that the entropy of suboptimality gaps governs the sample complexity needed to identify the best arm.

best-arm-identification fixed-confidence-setting gap-entropy-conjecture machine-learning-theory multi-armed bandits sample-complexity

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arXiv cs.LGA positive resolution of the gap-entropy conjecture ↗SEP 10 04:00 UTC