AI RESEARCH
Bayesian Optimization of Partially Known Systems using Hybrid Models
arXiv CS.LG
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ArXi:2603.11199v1 Announce Type: new Bayesian optimization (BO) has gained attention as an efficient algorithm for black-box optimization of expensive-to-evaluate systems, where the BO algorithm iteratively queries the system and suggests new trials based on a probabilistic model fitted to previous samples. Still, the standard BO loop may require a prohibitively large number of experiments to converge to the optimum, especially for high-dimensional and nonlinear systems.