The Convergence of Contrastive Divergences

  title={The Convergence of Contrastive Divergences},
  author={Alan L. Yuille},
This paper analyses the Contrastive Divergence algorithm for learning statistical parameters. We relate the algorithm to the stochastic approximation literature. This enables us to specify conditions under which the algorithm is guaranteed to converge to the optimal solution. This includes necessary and sufficient conditions for the solution to be unbiased. Category: Learning Theory 
Highly Cited
This paper has 111 citations. REVIEW CITATIONS



Citations per Year

112 Citations

Semantic Scholar estimates that this publication has 112 citations based on the available data.

See our FAQ for additional information.