0478631 - ÚI 2018 RIV DE eng C - Conference Paper (international conference)
Repický, Jakub - Bajer, Lukáš - Pitra, Zbyněk - Holeňa, MartinAdaptive Generation-Based Evolution Control for Gaussian Process Surrogate Models.
Proceedings ITAT 2017: Information Technologies - Applications and Theory. Aachen & Charleston: Technical University & CreateSpace Independent Publishing Platform, 2017 - (Hlaváčová, J.), s. 136-143. CEUR Workshop Proceedings, V-1885. ISBN 978-1974274741. ISSN 1613-0073.
[ITAT 2017. Conference on Theory and Practice of Information Technologies - Applications and Theory /17./. Martinské hole (SK), 22.09.2017-26.09.2017]
R&D Projects: GA ČR GA17-01251S
Grant - others:GA MŠk(CZ) LM2015042
Institutional support: RVO:67985807
Keywords : black-box optimization * evolutionary optimization * surrogate modelling * Gaussian process * CMA-ES
OECD category: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
http://ceur-ws.org/Vol-1885/136.pdf
Permanent Link: http://hdl.handle.net/11104/0274761
