arXiv Statistics ML
Acquisition for Spherical-Linear Bayesian Optimization on the Cube
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Exploiting Separability in Multi-Scale Grey-Box Bayesian Optimization
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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Towards Regret Guarantees for One-Step Lookahead Bayesian Optimization
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Bayesian Optimisation Using Product-of-Experts Gaussian Process Models with Uncertainty Calibration
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BONSAI: Bayesian Optimization with Natural Simplicity and Interpretability
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How Many Initial Points Does Bayesian Optimization Need?
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arXiv Machine Learning
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Pre-training of Bayesian Optimization Algorithm through Bayesian Optimization
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