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  1. 1.
    0509320 - ÚI 2020 RIV DE eng C - Conference Paper (international conference)
    Pitra, Zbyněk - Bajer, Lukáš - Holeňa, Martin
    Knowledge-based Selection of Gaussian Process Surrogates.
    IAL ECML PKDD 2019: Workshop & Tutorial on Interactive Adaptive Learning. Proceedings. Aachen: Technical University & CreateSpace Independent Publishing Platform, 2019 - (Kottke, D.; Lemaire, D.; Calma, A.; Krempl, G.; Holzinger, A.), s. 48-63. CEUR Workshop Proceedings, 2444. ISSN 1613-0073.
    [ECML PKDD 2019: The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases. Würzburg (DE), 16.09.2019-20.09.2019]
    R&D Projects: GA ČR GA17-01251S; GA ČR(CZ) GA18-18080S
    Grant - others:ČVUT(CZ) SGS17/193/OHK4/3T/14; GA MŠk(CZ) LM2015042
    Institutional support: RVO:67985807
    Keywords : Benchmarking * Black-box optimization * Gaussian process * Landscape analysis
    OECD category: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
    http://ceur-ws.org/Vol-2444/ialatecml_paper4.pdf
    Permanent Link: http://hdl.handle.net/11104/0300063
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  2. 2.
    0494112 - ÚI 2019 RIV DE eng C - Conference Paper (international conference)
    Pitra, Zbyněk - Repický, Jakub - Holeňa, Martin
    Boosted Regression Forest for the Doubly Trained Surrogate Covariance Matrix Adaptation Evolution Strategy.
    ITAT 2018: Information Technologies – Applications and Theory. Proceedings of the 18th conference ITAT 2018. Aachen: Technical University & CreateSpace Independent Publishing Platform, 2018 - (Krajči, S.), s. 72-79. CEUR Workshop Proceedings, V-2203. ISSN 1613-0073.
    [ITAT 2018. Conference on Information Technologies – Applications and Theory /18./. Plejsy (SK), 21.09.2018-25.09.2018]
    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 : Gradient boosting * Random forest * Black-box optimization * Surrogate model * Benchmarking
    OECD category: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
    http://ceur-ws.org/Vol-2203/72.pdf
    Permanent Link: http://hdl.handle.net/11104/0287361
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  3. 3.
    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/11104/0274762
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  4. 4.
    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/11104/0274013
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  5. 5.
    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/11104/0274009
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    a0477762.pdf2957 KBPublisher’s postprintrequire
     
     


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