126 search results - page 1 / 26 » Covariance estimation in decomposable Gaussian graphical mod... |
TSP
2010
13 years 20 hour 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...
ICASSP
2009
IEEE
13 years 9 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
2012
12 years 27 days ago
2012
—We consider distributed estimation of the inverse covariance matrix in Gaussian graphical models. These models factorize the multivariate distribution and allow for efficient d...
JMLR
2008
13 years 5 months ago
2008
In graphical modelling, a bi-directed graph encodes marginal independences among random variables that are identified with the vertices of the graph. We show how to transform a bi...
ICML
2006
IEEE
14 years 6 months ago
2006
IEEE
We consider the problem of fitting a large-scale covariance matrix to multivariate Gaussian data in such a way that the inverse is sparse, thus providing model selection. Beginnin...