33 search results - page 2 / 7 » Stable Principal Component Pursuit |
NIPS
2008
14 years 11 months ago
2008
We analyse matching pursuit for kernel principal components analysis (KPCA) by proving that the sparse subspace it produces is a sample compression scheme. We show that this bound...
102
click to vote
JACM
2011
14 years 12 days ago
2011
This paper is about a curious phenomenon. Suppose we have a data matrix, which is the superposition of a low-rank component and a sparse component. Can we recover each component i...
BMCBI
2010
14 years 9 months ago
2010
Background: Principal component analysis (PCA) has gained popularity as a method for the analysis of highdimensional genomic data. However, it is often difficult to interpret the ...
ICPR
2002
IEEE
15 years 10 months ago
2002
IEEE
Manifold Pursuit (MP) extends Principal Component Analysis to be invariant to a desired group of image-plane transformations of an ensemble of un-aligned images. We derive a simpl...
94
Voted
AIPR
2002
IEEE
15 years 2 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 ...