Výsledky vyhledávání - "Kononova, A.V."

A systematic approach to analyze the computational cost of robustness in model-assisted robust optimization: a systematic approach to analyze the computational cost

Autor: Ullah, S., Wang, H., Menzel, S., Sendhoff, B., Bäck, T.H.W., Rudolph, G., Kononova, A.V., Aguirre, H., Kerschke, P., Ochoa, G., Tušar, T.

Publikováno v: Lecture notes in computer science (LNCS), 63-75. Cham: Springer
STARTPAGE=63;ENDPAGE=75;TITLE=Lecture notes in computer science (LNCS)

Real-world optimization scenarios under uncertainty and noise are typically handled with robust optimization techniques, which re-formulate the original optimization problem into a robust counterpart, e.g., by taking an average of the function values

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::d9dcbe1dcf8149c0a362d5f0a8db45f9
http://hdl.handle.net/1887/3463877

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Optimizing stimulus energy for cochlear implants with a machine learning model of the auditory nerve

Autor: Nobel, J.P. de, Kononova, A.V., Briaire, J.J., Frijns, J.H.M., Bäck, T.H.W.

Publikováno v: Hearing Research, 432. ELSEVIER

Performing simulations with a realistic biophysical auditory nerve fiber model can be very time-consuming, due to the complex nature of the calculations involved. Here, a surrogate (approximate) model of such an auditory nerve fiber model was develop

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3e0f982ad1cf454759f4ef6b943619db
http://hdl.handle.net/1887/3607996

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One-shot optimization for vehicle dynamics control systems

Autor: Thomaser, A.M., Kononova, A.V., Vogt, M., Bäck, T.H.W., Fieldsend, J.E.

Publikováno v: GECCO '22: Proceedings of the genetic and evolutionary computation conference companion, 2036-2045. ACM
STARTPAGE=2036;ENDPAGE=2045;TITLE=GECCO '22: Proceedings of the genetic and evolutionary computation conference companion

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cc1c380cc261a7cead441377ee26ec4a
https://doi.org/10.1145/3520304.3533979

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Using structural bias to analyse the behaviour of modular CMA-ES

Autor: Vermetten, D.L., Caraffini, F., Stein, B. van, Kononova, A.V., Fieldsend, J.E.

Publikováno v: GECCO '22: Proceedings of the genetic and evolutionary computation conference companion, 1674-1682. Boston: ACM
STARTPAGE=1674;ENDPAGE=1682;TITLE=GECCO '22: Proceedings of the genetic and evolutionary computation conference companion

The Covariance Matrix Adaptation Evolution Strategy (CMA-ES) is a commonly used iterative optimisation heuristic for optimising black-box functions. CMA-ES comes in many flavours with different configuration settings. In this work, we investigate whe

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::74a3df11cd511d7d7a9bb50398d37193
https://doi.org/10.1145/3520304.3534035

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Auto-REP: an automated regression pipeline approach for high-efficiency earthquake prediction using LANL data

Autor: Yang, F., Kefalas, M., Koch, M., Kononova, A.V., Qiao, Y., Bäck, T.H.W.

Publikováno v: 2022 14th International conference on computer and automation engineering ICCAE 2022, 127-134. IEEE
STARTPAGE=127;ENDPAGE=134;TITLE=2022 14th International conference on computer and automation engineering ICCAE 2022

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::24c877369002a424a1874028910734dc
http://hdl.handle.net/1887/3505508

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Akademický článek

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Analysis of structural bias in Differential Evolution configurations

Autor: Vermetten, D.L., Stein, B. van, Kononova, A.V., Caraffini, F., Kumar, B.V., Oliva, D., Suganthan, P.N

Publikováno v: Studies in Computational Intelligence, 1-22. Singapore: Springer
STARTPAGE=1;ENDPAGE=22;TITLE=Studies in Computational Intelligence
Studies in Computational Intelligence ISBN: 9789811680816

Differential Evolution is a popular optimisation method with a small number of parameters. However, different hyper-parameters and Differential Evolution variants such as different mutation operators and the F and Cr parameter may introduce structura

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c42429d91104da44ffd7730d7e3256f5
https://doi.org/10.1007/978-981-16-8082-3_1

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Quantifying the impact of boundary constraint handling methods on differential evolution

Autor: Boks, R., Kononova, A.V., Wang, H., Chicano, F.

Publikováno v: GECCO Companion
GECCO '21: Proceedings of the Genetic and Evolutionary Computation Conference, 1199-1207. New York, U.S.A.: ACM
STARTPAGE=1199;ENDPAGE=1207;TITLE=GECCO '21: Proceedings of the Genetic and Evolutionary Computation Conference

Constraint handling is one of the most influential aspects of applying metaheuristics to real-world applications, which can hamper the search progress if treated improperly. In this work, we focus on a particular case - the box constraints, for which

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b83a25a354ca7e9e879cb074a7206ae1
https://doi.org/10.1145/3449726.3463214

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Addressing the Multiplicity of Solutions in Optical Lens Design as a Niching Evolutionary Algorithms Computational Challenge

Autor: Kononova, A.V., Shir, O.M., Tukker, T., Frisco, P., Zeng, S., Bäck, T.H.W., Chicano, F.

Publikováno v: GECCO Companion
GECCO'21: Proceedings of the Genetic and Evolutionary Computation Conference Companion, 1596-1604. ACM
STARTPAGE=1596;ENDPAGE=1604;TITLE=GECCO'21: Proceedings of the Genetic and Evolutionary Computation Conference Companion

Optimal Lens Design constitutes a fundamental, long-standing real-world optimization challenge. Potentially large number of optima, rich variety of critical points, as well as solid understanding of certain optimal designs per simple problem instance

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e38bd522adc9b3e51a58116ea6537815
http://arxiv.org/abs/2105.10541

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