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- 1.0478629 - ÚI 2018 RIV DE eng C - Conference Paper (international conference)
Pitra, Zbyněk - Bajer, Lukáš - Repický, Jakub - Holeňa, Martin
Adaptive Doubly Trained Evolution Control for the Covariance Matrix Adaptation Evolution Strategy.
Proceedings ITAT 2017: Information Technologies - Applications and Theory. Aachen & Charleston: Technical University & CreateSpace Independent Publishing Platform, 2017 - (Hlaváčová, J.), s. 120-128. 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:ČVUT(CZ) SGS17/193/OHK4/3T/14; GA MŠk(CZ) LO1611; GA MŠk(CZ) LM2010005
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-1885/120.pdf
Permanent Link: http://hdl.handle.net/11104/0274762File Download Size Commentary Version Access a0478629.pdf 5 1.2 MB Publisher’s postprint require - 2.0477789 - ÚI 2018 RIV US eng C - Conference Paper (international conference)
Pitra, Z. - Bajer, L. - Repický, J. - Holeňa, Martin
Comparison of Ordinal and Metric Gaussian Process Regression as Surrogate Models for CMA Evolution Strategy.
GECCO 2017. Proceedings of the Genetic and Evolutionary Computation Conference Companion. New York: ACM, 2017, s. 1764-1771. ISBN 978-1-4503-4939-0.
[GECCO 2017. Genetic and Evolutionary Computation Conference. Berlin (DE), 15.07.2017-19.07.2017]
R&D Projects: GA ČR GA17-01251S
Grant - others:GA MŠk(CZ) LO1611; ČVUT(CZ) SGS17/193/OHK4/3T/14; GA MŠk(CZ) LM2010005
Institutional support: RVO:67985807
Keywords : black-box optimization * evolutionary optimization * surrogate modelling * Gaussian-process regression
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/11104/0274013File Download Size Commentary Version Access a0477789.pdf 1 1.2 MB Publisher’s postprint require - 3.0477762 - ÚI 2018 RIV US eng C - Conference Paper (international conference)
Pitra, Z. - Bajer, L. - Repický, J. - Holeňa, Martin
Overview of Surrogate-model Versions of Covariance Matrix Adaptation Evolution Strategy.
GECCO 2017. Proceedings of the Genetic and Evolutionary Computation Conference Companion. New York: ACM, 2017, s. 1622-1629. ISBN 978-1-4503-4939-0.
[GECCO 2017. Genetic and Evolutionary Computation Conference. Berlin (DE), 15.07.2017-19.07.2017]
R&D Projects: GA ČR GA17-01251S
Grant - others:GA MŠk(CZ) LO1611; ČVUT(CZ) SGS17/193/OHK4/3T/14; GA MŠk(CZ) LM2010005
Institutional support: RVO:67985807
Keywords : black-box optimization * evolutionary optimization * surrogate modelling
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/11104/0274009File Download Size Commentary Version Access a0477762.pdf 2 957 KB Publisher’s postprint require - 4.0473143 - ÚI 2018 RIV CH eng C - Conference Paper (international conference)
Kalina, Jan - Hlinka, Jaroslav
Implicitly Weighted Robust Classification Applied to Brain Activity Research.
Biomedical Engineering Systems and Technologies. Cham: Springer, 2017 - (Fred, A.; Gamboa, H.), s. 87-107. Communications in Computer and Information Science, 690. ISBN 978-3-319-54716-9. ISSN 1865-0929.
[BIOSTEC 2016 International Joint Conference /9./. Rome (IT), 21.02.2016-23.02.2016]
R&D Projects: GA ČR GA13-23940S
Grant - others:GA MŠk(CZ) LO1611; Nadační fond na podporu vědy(CZ) Neuron
Institutional support: RVO:67985807
Keywords : high-dimensional data * classification analysis * robustness * outliers * regularization
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/11104/0270309File Download Size Commentary Version Access a0473143.pdf 2 315.9 KB Publisher’s postprint require - 5.0466878 - ÚI 2017 RIV CH eng C - Conference Paper (international conference)
Pitra, Zbyněk - Bajer, L. - Holeňa, Martin
Doubly Trained Evolution Control for the Surrogate CMA-ES.
Parallel Problem Solving from Nature - PPSN XIV. Cham: Springer, 2016 - (Handl, J.; Hart, E.; Lewis, P.; López-Ibáñez, M.; Ochoa, G.; Paechter, B.), s. 59-68. Lecture Notes in Computer Science, 9921. ISBN 978-3-319-45822-9. ISSN 0302-9743.
[PPSN XIV. International Conference on Parallel Problem Solving from Nature /14./. Edinburgh (GB), 17.09.2016-21.09.2016]
R&D Projects: GA MZd(CZ) NV15-33250A
Grant - others:ČVUT(CZ) SGS14/205/OHK4/3T/14; GA MŠk(CZ) ED2.1.00/03.0078; GA MŠk(CZ) LO1611; GA MŠk(CZ) LM2010005
Institutional support: RVO:67985807
Keywords : black-box optimization * surrogate model * evolution control * Gaussian process
Subject RIV: IN - Informatics, Computer Science
Permanent Link: http://hdl.handle.net/11104/0265826File Download Size Commentary Version Access a0466878.pdf 2 449.1 KB Publisher’s postprint require