arXiv Machine Learning August 5, 2026 By Joshua E. Hammond, Tyler A. Soderstrom, Brian A. Korgel, Michael Baldea

Exploiting Separability in Multi-Scale Grey-Box Bayesian Optimization

Read the original on arXiv Machine Learning →

arXiv:2608. 03045v1 Announce Type: new Abstract: We consider grey-box optimization problems where the decision variables naturally partition into black-box variables (as arguments to an expensive black-box function) and white-box variables, governed by a set of explicit, closed-form equations that also depend on the output of the black-box function.

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