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arXiv · 2310.10614

Understanding an Acquisition Function Family for Bayesian Optimization

Jiajie Kong·Tony Pourmohamad·Herbert K. H. Lee
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Abstract

Bayesian optimization (BO) developed as an approach for the efficient optimization of expensive black-box functions without gradient information. A typical BO paper introduces a new approach and compares it to some alternatives on simulated and possibly real examples to show its efficacy. Yet on a different example, this new algorithm might not be as effective as the alternatives. This paper looks at a broader family of approaches to explain the strengths and weaknesses of algorithms in the family, with guidance on what choices might work best on different classes of problems.

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BibTeXRIS

Jiajie Kong, Tony Pourmohamad, Herbert K. H. Lee. 2023-10-16. Understanding an Acquisition Function Family for Bayesian Optimization. https://arxiv.org/abs/2310.10614

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