13 search results - page 2 / 3 » Laplace Propagation |
UAI
2001
13 years 6 months ago
2001
This paper presents a new deterministic approximation technique in Bayesian networks. This method, "Expectation Propagation," unifies two previous techniques: assumed-de...
JMLR
2010
12 years 11 months ago
2010
The GPML toolbox provides a wide range of functionality for Gaussian process (GP) inference and prediction. GPs are specified by mean and covariance functions; we offer a library ...
ICML
2004
IEEE
14 years 5 months ago
2004
IEEE
In many real-world classification problems the input contains a large number of potentially irrelevant features. This paper proposes a new Bayesian framework for determining the r...
JMLR
2008
13 years 4 months ago
2008
The linear model with sparsity-favouring prior on the coefficients has important applications in many different domains. In machine learning, most methods to date search for maxim...
ECML
2007
Springer
13 years 11 months ago
2007
Springer
We present a framework for efficient, accurate approximate Bayesian inference in generalized linear models (GLMs), based on the expectation propagation (EP) technique. The paramete...