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#machine learning Preprint May 2026

Regret-Based $(\epsilon,\delta)$-optimal Stopping Criteria for Bayesian Optimization

This work presents provably tighter instantaneous regret bounds for GP upper confidence bound (GP-UCB) at any given iteration and proposes stopping criteria for GP-UCB based on this tighter bound that ensures an $\epsilon$-optimal solution with high probability $1-\delta$ upon termination.

Hao-Wei Wang, Jingyi Wang, Qi-Yu Wei · 0 citations

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