Laplace Propagation

9 years 8 months ago
Laplace Propagation
We present a novel method for approximate inference in Bayesian models and regularized risk functionals. It is based on the propagation of mean and variance derived from the Laplace approximation of conditional probabilities in factorizing distributions, much akin to Minka’s Expectation Propagation. In the jointly normal case, it coincides with the latter and belief propagation, whereas in the general case, it provides an optimization strategy containing Support Vector chunking, the Bayes Committee Machine, and Gaussian Process chunking as special cases.
Alexander J. Smola, Vishy Vishwanathan, Eleazar Es
Added 31 Oct 2010
Updated 31 Oct 2010
Type Conference
Year 2003
Where NIPS
Authors Alexander J. Smola, Vishy Vishwanathan, Eleazar Eskin
Comments (0)