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- 1.0477787 - ÚI 2018 US eng A - Abstract
Pitra, Z. - Bajer, L. - Repický, J. - Holeňa, Martin
Ordinal versus metric gaussian process regression in surrogate modelling for CMA evolution strategy.
GECCO 2017. Proceedings of the Genetic and Evolutionary Computation Conference Companion. New York: ACM, 2017. s. 177-178. ISBN 978-1-4503-4939-0.
[GECCO 2017. Genetic and Evolutionary Computation Conference. 15.07.2017-19.07.2017, Berlin]
R&D Projects: GA ČR GA17-01251S
Grant - others:GA MŠk(CZ) LO1611; ČVUT(CZ) SGS17/193/OHK4/3T/14
Institutional support: RVO:67985807
Keywords : black-box optimization * evolutionary optimization * surrogate modelling * Gaussian-process regression
Subject RIV: IN - Informatics, Computer Science
Permanent Link: http://hdl.handle.net/11104/0274011File Download Size Commentary Version Access a0477787.pdf 2 668.9 KB Publisher’s postprint require - 2.0330008 - ÚI 2010 SK eng A - Abstract
Bajer, L. - Holeňa, Martin
Improving Genetic Optimization by Means of Radial Basis Function Networks.
Informačné technológie - Aplikácie a teória. Seňa: Pont, 2009 - (Vojtáš, P.). s. 95-96. ISBN 978-80-970179-1-0.
[ITAT 2009. Conference on Theory and Practice of Information Theory. 25.09.2009-29.09.2009, Kráľova studňa]
Institutional research plan: CEZ:AV0Z10300504
Keywords : black-box optimization * evolutionary optimization * genetic algorithms * surrogate modelling * radial basis function networks
Subject RIV: IN - Informatics, Computer Science
Permanent Link: http://hdl.handle.net/11104/0175885File Download Size Commentary Version Access 0330008.pdf 2 749.7 KB Author´s preprint open-access 0330008_poster.pdf 1 811.7 KB Other open-access