38 search results - page 2 / 8 » Boosting and Maximum Likelihood for Exponential Models |
ACL
2006
13 years 6 months ago
2006
Lasso is a regularization method for parameter estimation in linear models. It optimizes the model parameters with respect to a loss function subject to model complexities. This p...
IJAR
2010
13 years 3 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 ...
JSC
2006
13 years 5 months ago
2006
In statistics, mixture models consisting of several component subpopulations are used widely to model data drawn from heterogeneous sources. In this paper, we consider maximum lik...
ICML
2007
IEEE
14 years 6 months ago
2007
IEEE
Conditional log-linear models are a commonly used method for structured prediction. Efficient learning of parameters in these models is therefore an important problem. This paper ...
ML
2008
ACM
13 years 5 months ago
2008
ACM
The use of Bayesian networks for classification problems has received significant recent attention. Although computationally efficient, the standard maximum likelihood learning me...