6 search results - page 1 / 2 » A skew Gaussian decomposable graphical model |
ICASSP
2009
IEEE
13 years 8 months ago
2009
IEEE
We consider principal component analysis (PCA) in decomposable Gaussian graphical models. We exploit the prior information in these models in order to distribute its computation. ...
TSP
2010
12 years 11 months ago
2010
Graphical models are a framework for representing and exploiting prior conditional independence structures within distributions using graphs. In the Gaussian case, these models are...
JMLR
2006
13 years 4 months ago
2006
We present a new framework based on walks in a graph for analysis and inference in Gaussian graphical models. The key idea is to decompose the correlation between each pair of var...
BMCBI
2010
13 years 5 months ago
2010
Background: Chow and Liu showed that the maximum likelihood tree for multivariate discrete distributions may be found using a maximum weight spanning tree algorithm, for example K...
GECCO
2007
Springer
13 years 11 months ago
2007
Springer
In this paper we propose a genetic programming approach to learning stochastic models with unsymmetrical noise distributions. Most learning algorithms try to learn from noisy data...