59 search results - page 5 / 12 » Compressive Principal Component Pursuit |
ISCAS
1999
IEEE
15 years 1 months ago
1999
IEEE
The problem of optimization of subband coders for given input statistics has received considerable attention in recent literature. The goal in these works has been to maximize the...
ICIP
2004
IEEE
15 years 11 months ago
2004
IEEE
We propose a mixture of multiple linear models, also known as hybrid linear model, for a sparse representation of an image. This is a generalization of the conventional KarhunenLo...
NN
2000
Springer
14 years 9 months ago
2000
Springer
A fundamental problem in neural network research, as well as in many other disciplines, is finding a suitable representation of multivariate data, i.e. random vectors. For reasons...
87
Voted
SDM
2007
SIAM
14 years 11 months ago
2007
SIAM
We propose an efficient algorithm for principal component analysis (PCA) that is applicable when only the inner product with a given vector is needed. We show that Krylov subspace...
ICPR
2010
IEEE
14 years 11 months ago
2010
IEEE
In this paper we investigate the usage of random ortho-projections in the compression of sparse feature vectors. The study is carried out by evaluating the compressed features in ...