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Model guided sampling optimization with gaussian processes for expensive black-box optimization
- 1.0394260 - ÚI 2014 RIV US eng C - Conference Paper (international conference)
Bajer, Lukáš - Charypar, V. - Holeňa, Martin
Model guided sampling optimization with gaussian processes for expensive black-box optimization.
GECCO Companion '13. Proceeding of the fifteenth annual conference companion on Genetic and evolutionary computation conference companion. New York: ACM, 2013 - (Blum, C.), s. 1715-1716. ISBN 978-1-4503-1964-5.
[GECCO 2013. Genetic and Evolutionary Computation Conference. Amsterdam (NL), 06.07.2013-10.07.2013]
R&D Projects: GA ČR GAP202/11/1368; GA ČR GA13-17187S
Grant - others:GA UK(CZ) 278511/2011; CTU(CZ) SGS12/196/OHK3/3T/14
Institutional support: RVO:67985807
Keywords : benchmarking * black-box optimization * modelling * gaussian processes
Subject RIV: IN - Informatics, Computer Science
Model Guided Sampling Optimization (MGSO) is a novel expensive black-box optimization method based on a combination of ideas from Estimation of Distribution Algorithms and global optimization methods using Gaussian Processes. The algorithm is described and its implementation tested on three benchmark functions as a proof of concept.
Permanent Link: http://hdl.handle.net/11104/0222531
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