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0506867 - ÚI 2020 RIV US eng A - Abstract
Bajer, Lukáš - Pitra, Zbyněk - Repický, Jakub - Holeňa, Martin
Gaussian Process Surrogate Models for the CMA-ES.
GECCO '19. Proceedings of the Genetic and Evolutionary Computation Conference Companion. New York: ACM, 2019. s. 17-18. ISBN 978-1-4503-6748-6.
[GECCO 2019: The Genetic and Evolutionary Computation Conference. 13.07.2019-17.07.2019, Prague]
R&D Projects: GA ČR GA17-01251S; GA ČR(CZ) GA18-18080S
Institutional support: RVO:67985807
Keywords : black-box optimization * evolutionary optimization * surrogate modelling * Gaussian process
OECD category: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Permanent Link: http://hdl.handle.net/11104/0298001