847 search results - page 25 / 170 » HITS is Principal Components Analysis |
169
Voted
ICIP
2008
IEEE
16 years 2 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
15 years 15 days 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...
148
Voted
CORR
2012
Springer
13 years 8 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...
124
Voted
CIKM
2010
Springer
14 years 11 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...
112
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IJCNN
2000
IEEE
15 years 4 months 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...