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Gradient-based Sample Selection for Faster Bayesian Optimization

This story is from 2026-08-27. It is preserved in the archive; the latest stories are on the live feed.

arXiv:2504.07742v4 Announce Type: replace Abstract: Bayesian optimization (BO) is an effective technique for black-box optimization. However, its applicability is typically limited to moderate-budget problems due to the cubic complexity of fitting the Gaussian process (GP) surrogate model. In large…

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  1. 2026-08-27 04:00 · arXiv stat.ML
    Gradient-based Sample Selection for Faster Bayesian Optimization

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