• DocumentCode
    3493210
  • Title

    Regularisation of mixture density networks

  • Author

    Hjorth, Lars U. ; Nabney, Ian T.

  • Author_Institution
    Neural Comput. Res. Group, Aston Univ., Birmingham, UK
  • Volume
    2
  • fYear
    1999
  • fDate
    1999
  • Firstpage
    521
  • Abstract
    Mixture density networks (MDNs) are a well-established method for modelling complex multi-valued functions where regression methods (such as MLPs) fail. In this paper we develop a Bayesian regularisation method for MDNs by an extension of the evidence procedure. The method is tested on two data sets and compared with early stopping
  • Keywords
    neural nets; Bayesian regularisation; maximum likelihood estimation; mixture density networks; multivalued functions; neural networks; probability;
  • fLanguage
    English
  • Publisher
    iet
  • Conference_Titel
    Artificial Neural Networks, 1999. ICANN 99. Ninth International Conference on (Conf. Publ. No. 470)
  • Conference_Location
    Edinburgh
  • ISSN
    0537-9989
  • Print_ISBN
    0-85296-721-7
  • Type

    conf

  • DOI
    10.1049/cp:19991162
  • Filename
    817982
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3493210