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Supervised Learning Errors by Radial Basis Function Neural Networks and Regularization Networks

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985807%3A_____%2F08%3A00331008" target="_blank" >RIV/67985807:_____/08:00331008 - isvavai.cz</a>

  • Result on the web

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Supervised Learning Errors by Radial Basis Function Neural Networks and Regularization Networks

  • Original language description

    There is a gap between the theoretical results of regularization theory and practical suitability of regularization derived networks (RN). On the other hand, radial basis function networks (RBF) that can be seen as a special case of regularization networks, have a rich selection of learning algorithms. In this work we study a relationship between RN and RBF, and show that theoretical estimates for RN hold for a concrete RBF applied on real-world data.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

    IN - Informatics

  • OECD FORD branch

Result continuities

  • Project

    <a href="/en/project/GA201%2F08%2F1744" target="_blank" >GA201/08/1744: Complexity of perceptron and kernel networks</a><br>

  • Continuities

    Z - Vyzkumny zamer (s odkazem do CEZ)

Others

  • Publication year

    2008

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    Proceedings of Second International Conference on Future Generation Communication and Networking Symposia

  • ISBN

    978-1-4244-3430-5

  • ISSN

  • e-ISSN

  • Number of pages

    4

  • Pages from-to

  • Publisher name

    IEEE Computer Society

  • Place of publication

    Los Alamitos

  • Event location

    Hainan Island

  • Event date

    Dec 13, 2008

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article

    000270432000079