Connections between score matching, contrastive divergence, and pseudolikelihood for continuous-valued variables

IEEE Trans Neural Netw. 2007 Sep;18(5):1529-31. doi: 10.1109/tnn.2007.895819.

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.

Publication types

  • Letter
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms*
  • Artificial Intelligence*
  • Computer Simulation
  • Likelihood Functions
  • Models, Statistical*
  • Pattern Recognition, Automated / methods*