53 search results - page 3 / 11 » Expectation Propagation for approximate Bayesian inference |
UAI
2003
13 years 6 months ago
2003
Loopy and generalized belief propagation are popular algorithms for approximate inference in Markov random fields and Bayesian networks. Fixed points of these algorithms correspo...
JMLR
2008
13 years 5 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...
NIPS
2007
13 years 6 months ago
2007
Generalized linear models are the most commonly used tools to describe the stimulus selectivity of sensory neurons. Here we present a Bayesian treatment of such models. Using the ...
NIPS
2004
13 years 6 months ago
2004
We propose a novel a framework for deriving approximations for intractable probabilistic models. This framework is based on a free energy (negative log marginal likelihood) and ca...
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...