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  1. 1.
    0577075 - ÚI 2024 RIV CH eng C - Conference Paper (international conference)
    Kůrková, Věra
    Approximation of Binary-Valued Functions by Networks of Finite VC Dimension.
    Artificial Neural Networks and Machine Learning – ICANN 2023. Proceedings, Part I. Cham: Springer, 2023 - (Iliadis, L.; Papaleonidas, A.; Angelov, P.; Jayne, C.), s. 483-490. Lecture Notes in Computer Science, 14254. ISBN 978-3-031-44206-3. ISSN 0302-9743.
    [ICANN 2023: International Conference on Artificial Neural Networks /32./. Heraklion (GR), 26.09.2023-29.09.2023]
    R&D Projects: GA ČR(CZ) GA22-02067S
    Institutional support: RVO:67985807
    Keywords : approximation by neural networks * bounds on approximation errors * VC dimension * growth function * high-dimensional probability * concentration inequalities * method of bounded differences
    OECD category: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
    https://dx.doi.org/10.1007/978-3-031-44207-0_40
    Permanent Link: https://hdl.handle.net/11104/0346341
     
     
  2. 2.
    0572576 - ÚI 2024 RIV GB eng J - Journal Article
    Kůrková, Věra - Sanguineti, M.
    Approximation of Classifiers by Deep Perceptron Networks.
    Neural Networks. Roč. 165, August 2023 (2023), s. 654-661. ISSN 0893-6080. E-ISSN 1879-2782
    R&D Projects: GA ČR(CZ) GA22-02067S
    Institutional support: RVO:67985807
    Keywords : Approximation by deep networks * Probabilistic bounds on approximation errors * Random classifiers * Concentration of measure * Method of bounded differences * Growth functions
    OECD category: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
    Impact factor: 7.8, year: 2022
    Method of publishing: Limited access
    https://dx.doi.org/10.1016/j.neunet.2023.06.004
    Permanent Link: https://hdl.handle.net/11104/0343221
     
     
  3. 3.
    0543168 - ÚI 2022 RIV DE eng J - Journal Article
    Kůrková, Věra - Sanguineti, M.
    Correlations of Random Classifiers on Large Data Sets.
    Soft Computing. Roč. 25, č. 19 (2021), s. 12641-12648. ISSN 1432-7643. E-ISSN 1433-7479
    R&D Projects: GA ČR(CZ) GA19-05704S
    Institutional support: RVO:67985807
    Keywords : Random classifiers * Optimization of feedforward networks * Binary classification * Concentration of measure * Method of bounded differences
    OECD category: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
    Impact factor: 3.732, year: 2021
    Method of publishing: Limited access
    http://dx.doi.org/10.1007/s00500-021-05938-4
    Permanent Link: http://hdl.handle.net/11104/0320443
     
     


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