63 search results - page 3 / 13 » Principal component analysis in decomposable Gaussian graphi... |
AIPR
2002
IEEE
13 years 11 months ago
2002
IEEE
Conventional remote sensing classification techniques that model the data in each class with a multivariate Gaussian distribution are inefficient, as this assumption is generally ...
JMLR
2010
13 years 1 months ago
2010
Bayesian principal component analysis (BPCA), a probabilistic reformulation of PCA with Bayesian model selection, is a systematic approach to determining the number of essential p...
BMCBI
2010
13 years 6 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...
JMLR
2010
13 years 1 months ago
2010
In time series analysis, inference about causeeffect relationships among multiple times series is commonly based on the concept of Granger causality, which exploits temporal struc...
CORR
2010
Springer
13 years 6 months ago
2010
Springer
Suppose a given observation matrix can be decomposed as the sum of a low-rank matrix and a sparse matrix (outliers), and the goal is to recover these individual components from th...