Sequential model based optimization with black-box constraints: Feasibility determination via machine learning

This paper presents a Sequential M odel Based Optimization framework for optimizing black-box expensive objective functions where feasibile search space is unknown a-priori. The framework is organized in two phases, the first uses M achine Learning (a Support Vector M achine classifier) to approxima...

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Bibliographische Detailangaben

Hauptverfasser:	Candelieri, Antonio, Archetti, Francesco
Format:	Tagungsbericht
Sprache:	eng
Schlagworte:	Bayesian analysis Constraint modelling Feasibility Global optimization Machine learning
Online-Zugang:	Volltext
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