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Building kriging models using hierarchical codes with different levels of acc...
This paper deals with the Gaussian process based approximation of a code which can be run at different levels of accuracy using co-kriging. This method allows us to... -
Bayesian analysis of hierarchical multi-fidelity codes.
This paper deals with the Gaussian process based approximation of a code which can be run at different levels of accuracy. This method, which is a particular case of co-kriging,... -
Optimisation robuste multiobjectifs par modèles de substitution
This PhD thesis deals with the optimization under uncertainty of expensive functions in the context of aeronautical systems design. First, we develop a multiobjective... -
Meta-models for structural reliability and uncertainty quantification
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Self-Adaptive Surrogate-Assisted Covariance Matrix Adaptation Evolution Strategy
International audience -
Black-box optimization benchmarking of IPOP-saACM-ES and BIPOP-saACM-ES on th...
International audience -
Black-box optimization benchmarking of IPOP-saACM-ES on the BBOB-2012 noisy t...
International audience -
Planification d'expériences séquentielle dans un contexte de méta-modélisatio...
Large computer codes are widely used in engineering to study physical systems. Nevertheless, simulations can sometimes be time-consuming. In this case, an... -
Recursive co-kriging model for Design of Computer experiments with multiple l...
In many practical cases, a sensitivity analysis or an optimization of a complex time consuming computer code requires to build a fast running approximation of it -... -
BI-population CMA-ES Algorithms with Surrogate Models and Line Searches
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Surrogate-Assisted Evolutionary Algorithms
Evolutionary Algorithms (EAs) have received a lot of attention regarding their potential to solve complex optimization problems using problem-specific variation...
