12 search results - page 1 / 3 » High Dimensional Inverse Covariance Matrix Estimation via Li... |
JMLR
2010
12 years 11 months ago
2010
This paper considers the problem of estimating a high dimensional inverse covariance matrix that can be well approximated by "sparse" matrices. Taking advantage of the c...
CORR
2010
Springer
13 years 3 months ago
2010
Springer
Gaussian graphical models are of great interest in statistical learning. Because the conditional independencies between different nodes correspond to zero entries in the inverse c...
CVPR
2008
IEEE
14 years 6 months ago
2008
IEEE
We consider the task of dimensionality reduction for regression (DRR) whose goal is to find a low dimensional representation of input covariates, while preserving the statistical ...
BMCBI
2011
12 years 11 months ago
2011
Background: Typical analysis of microarray data ignores the correlation between gene expression values. In this paper we present a model for microarray data which specifically all...
CVPR
2008
IEEE
14 years 6 months ago
2008
IEEE
Linear inverse problems in computer vision, including motion estimation, shape fitting and image reconstruction, give rise to parameter estimation problems with highly correlated ...