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Evolving Sum and Composite Kernel Functions for Regularization Networks

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985807%3A_____%2F11%3A00359155" target="_blank" >RIV/67985807:_____/11:00359155 - isvavai.cz</a>

  • Result on the web

    <a href="http://dx.doi.org/10.1007/978-3-642-20282-7_19" target="_blank" >http://dx.doi.org/10.1007/978-3-642-20282-7_19</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1007/978-3-642-20282-7_19" target="_blank" >10.1007/978-3-642-20282-7_19</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Evolving Sum and Composite Kernel Functions for Regularization Networks

  • Original language description

    In this paper we propose a novel evolutionary algorithm for regularization networks. The main drawback of regularization networks in practical applications is the presence of meta-parameters, including the type and parameters of kernel functions Our learning algorithm provides a solution to this problem by searching through a space of different kernel functions, including sum and composite kernels. Thus, an optimal combination of kernel functions with parameters is evolved for given task specified by training data. Comparisons of composite kernels, single kernels, and traditional Gaussians are provided in several experiments.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

    IN - Informatics

  • OECD FORD branch

Result continuities

  • Project

    Result was created during the realization of more than one project. More information in the Projects tab.

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>Z - Vyzkumny zamer (s odkazem do CEZ)

Others

  • Publication year

    2011

  • Confidentiality

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

Data specific for result type

  • Article name in the collection

    Adaptive and Natural Computing Algorithms. Part I

  • ISBN

    978-3-642-20281-0

  • ISSN

  • e-ISSN

  • Number of pages

    10

  • Pages from-to

    180-189

  • Publisher name

    Springer

  • Place of publication

    Heidelberg

  • Event location

    Ljubljana

  • Event date

    Apr 14, 2011

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article

    000302389300019