149 search results - page 1 / 30 » Maximum Likelihood Learning of Conditional MTE Distributions |
ECSQARU
2009
Springer
13 years 11 months ago
2009
Springer
We describe a procedure for inducing conditional densities within the mixtures of truncated exponentials (MTE) framework. We analyse possible conditional MTE specifications and pr...
ICML
2005
IEEE
14 years 5 months ago
2005
IEEE
We introduce an expectation maximizationtype (EM) algorithm for maximum likelihood optimization of conditional densities. It is applicable to hidden variable models where the dist...
IJAR
2010
13 years 2 months ago
2010
Bayesian networks with mixtures of truncated exponentials (MTEs) support efficient inference algorithms and provide a flexible way of modeling hybrid domains (domains containing ...
ICML
2004
IEEE
14 years 5 months ago
2004
IEEE
Bayesian networks are a powerful probabilistic representation, and their use for classification has received considerable attention. However, they tend to perform poorly when lear...
IJCAI
2007
13 years 5 months ago
2007
While conditional random fields (CRFs) have been applied successfully in a variety of domains, their training remains a challenging task. In this paper, we introduce a novel trai...