0506867 - ÚI 2020 RIV US eng A - Abstrakt
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]
Grant CEP: GA ČR GA17-01251S; GA ČR(CZ) GA18-18080S
Institucionální podpora: RVO:67985807
Klíčová slova: black-box optimization * evolutionary optimization * surrogate modelling * Gaussian process
Obor OECD: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
DOI: https://doi.org/10.1145/3319619.3326764
Trvalý link: http://hdl.handle.net/11104/0298001