• DocumentCode
    1111705
  • Title

    Connections Between Score Matching, Contrastive Divergence, and Pseudolikelihood for Continuous-Valued Variables

  • Author

    Hyvärinen, Aapo

  • Author_Institution
    Helsinki Univ., Helsinki
  • Volume
    18
  • Issue
    5
  • fYear
    2007
  • Firstpage
    1529
  • Lastpage
    1531
  • Abstract
    Score matching (SM) and contrastive divergence (CD) are two recently proposed methods for estimation of nonnormalized statistical methods without computation of the normalization constant (partition function). Although they are based on very different approaches, we show in this letter that they are equivalent in a special case: in the limit of infinitesimal noise in a specific Monte Carlo method. Further, we show how these methods can be interpreted as approximations of pseudolikelihood.
  • Keywords
    Monte Carlo methods; maximum likelihood estimation; Monte Carlo method; continuous-valued variables; contrastive divergence; nonnormalized statistical methods estimation; normalization constant; pseudolikelihood approximations; score matching; Computer science; Information technology; Monte Carlo methods; Parameter estimation; Probability density function; Samarium; Statistical analysis; Normalization constant; partition function; statistical estimation; Algorithms; Artificial Intelligence; Computer Simulation; Likelihood Functions; Models, Statistical; Pattern Recognition, Automated;
  • fLanguage
    English
  • Journal_Title
    Neural Networks, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1045-9227
  • Type

    jour

  • DOI
    10.1109/TNN.2007.895819
  • Filename
    4298117