Search results
- 1.0506867 - 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 - 2.0493292 - ÚI 2019 RIV IE eng A - Abstract
Repický, Jakub - Pitra, Zbyněk - Holeňa, Martin
Adaptive Selection of Gaussian Process Model for Active Learning in Expensive Optimization.
ECML PKDD 2018: Workshop on Interactive Adaptive Learning. Proceedings. Dublin, 2018 - (Krempl, G.; Lemaire, V.; Kottke, D.; Calma, A.; Holzinger, A.; Polikar, R.; Sick, B.). s. 80-84
[ECML PKDD 2018: The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases. 10.09.2018-14.09.2018, Dublin]
R&D Projects: GA ČR GA17-01251S
Institutional support: RVO:67985807
Keywords : Gaussian process * Surrogate model * Black-box optimization * Active Learning
OECD category: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
https://www.ies.uni-kassel.de/p/ial2018/ialatecml2018.pdf
Permanent Link: http://hdl.handle.net/11104/0286678File Download Size Commentary Version Access a0493292.pdf 7 715 KB Sborník dostupný online. Publisher’s postprint open-access - 3.0493290 - ÚI 2019 RIV IE eng A - Abstract
Pitra, Zbyněk - Repický, Jakub - Holeňa, Martin
Transfer of Knowledge for Surrogate Model Selection in Cost-Aware Optimization.
ECML PKDD 2018: Workshop on Interactive Adaptive Learning. Proceedings. Dublin, 2018 - (Krempl, G.; Lemaire, V.; Kottke, D.; Calma, A.; Holzinger, A.; Polikar, R.; Sick, B.). s. 89-94
[ECML PKDD 2018: The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases. 10.09.2018-14.09.2018, Dublin]
R&D Projects: GA ČR GA17-01251S
Grant - others:ČVUT(CZ) SGS17/193/OHK4/3T/14; GA MŠk(CZ) LM2015042
Institutional support: RVO:67985807
Keywords : Metalearing * Surrogate model * Gaussian process * Random forest * Exploratory landscape analysis
OECD category: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
https://www.ies.uni-kassel.de/p/ial2018/ialatecml2018.pdf
Permanent Link: http://hdl.handle.net/11104/0286679File Download Size Commentary Version Access a0493290.pdf 23 568.2 KB Sborník dostupný online. Publisher’s postprint open-access