• DocumentCode
    329062
  • Title

    A mathematical foundation on Poggio´s regularization theory

  • Author

    Watanabe, Kôtarô ; Namatame, Akira ; Kashiwaghi, Eiichi

  • Author_Institution
    Dept. of Comput. Sci., Nat. Defense Acad., Yokosuka, Japan
  • Volume
    2
  • fYear
    1993
  • fDate
    25-29 Oct. 1993
  • Firstpage
    1717
  • Abstract
    This paper justifies the regularization theory for learning of an input-output mapping from a set of examples, which was proposed by Poggio. Moreover, the relationships between the dimension of input space, the restriction condition and the smoothness of the map obtained as a solution are proposed.
  • Keywords
    Hilbert spaces; learning (artificial intelligence); neural nets; Hilbert space; Poggio´s regularization theory; input space; input-output mapping; learning; neural nets; Boundary conditions; Computer science; Differential equations; Functional analysis; Laplace equations; Sufficient conditions;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 1993. IJCNN '93-Nagoya. Proceedings of 1993 International Joint Conference on
  • Print_ISBN
    0-7803-1421-2
  • Type

    conf

  • DOI
    10.1109/IJCNN.1993.716985
  • Filename
    716985
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=329062