159 search results - page 14 / 32 » Sparse non-Gaussian component analysis |
ISNN
2007
Springer
14 years 2 months ago
2007
Springer
Nonnegative Matrix and Tensor Factorization (NMF/NTF) and Sparse Component Analysis (SCA) have already found many potential applications, especially in multi-way Blind Source Separ...
CVPR
2008
IEEE
14 years 10 months ago
2008
IEEE
Sparse signal models have been the focus of much recent research, leading to (or improving upon) state-of-the-art results in signal, image, and video restoration. This article ext...
CORR
2012
Springer
12 years 4 months ago
2012
Springer
We consider the problem of recovering a target matrix that is a superposition of low-rank and sparse components, from a small set of linear measurements. This problem arises in co...
JMLR
2010
13 years 3 months ago
2010
Principal component analysis (PCA) is a classical data analysis technique that finds linear transformations of data that retain the maximal amount of variance. We study a case whe...
ICASSP
2009
IEEE
14 years 13 days 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. ...