1083 search results - page 29 / 217 » Robust principal component analysis |
ICIP
2008
IEEE
14 years 9 months ago
2008
IEEE
This paper presents an image denoising algorithm that uses principal component analysis (PCA) in conjunction with the non-local means image denoising. Image neighborhood vectors u...
CSDA
2008
13 years 7 months ago
2008
An important problem in principal component analysis (PCA) is the estimation of the correct number of components to retain. PCA is most often used to reduce a set of observed vari...
CORR
2012
Springer
12 years 3 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...
CIKM
2010
Springer
13 years 6 months ago
2010
Springer
Low-dimensional topic models have been proven very useful for modeling a large corpus of documents that share a relatively small number of topics. Dimensionality reduction tools s...
IJCNN
2000
IEEE
14 years 4 hour ago
2000
IEEE
Fuzzy c-varieties (FCV) is one of the clustering algorithms in which the prototypes are multi-dimensional linear varieties. The linear varieties are represented by some local prin...