Bayesian Optimization Using Simulation-Based Multiple Information Sources over Combinatorial Structures

Bayesian optimization due to its flexibility and sample efficiency has become a standard approach for simulation optimization. To reduce this problem, one can resort to cheaper surrogates of the objective function. Examples are ubiquitous, from protein engineering or material science to tuning machi...

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Bibliographic Details
Published in:	Machine learning and knowledge extraction Vol. 6; no. 4; pp. 2232 - 2247
Main Authors:	Sabbatella, Antonio, Ponti, Andrea, Candelieri, Antonio, Archetti, Francesco
Format:	Journal Article
Language:	English
Published:	Basel MDPI AG 01.12.2024
Subjects:	Algorithms Approximation Bayesian analysis Bayesian optimization Combinatorial analysis combinatorial optimization Comparative analysis Computer simulation Energy consumption Epistemology Financial analysis Gaussian process Gaussian processes Information sources Machine learning Mathematical optimization multi-fidelity network design Optimization Partial differential equations Random variables simulation value-at-risk Italy
ISSN:	2504-4990, 2504-4990
Online Access:	Get full text
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