208 search results - page 20 / 42 » Robust Kernel Principal Component Analysis |
SSDBM
2008
IEEE
14 years 1 months ago
2008
IEEE
Abstract. Most correlation clustering algorithms rely on principal component analysis (PCA) as a correlation analysis tool. The correlation of each cluster is learned by applying P...
CORR
2010
Springer
13 years 7 months ago
2010
Springer
Suppose a given observation matrix can be decomposed as the sum of a low-rank matrix and a sparse matrix (outliers), and the goal is to recover these individual components from th...
ICIP
2007
IEEE
14 years 9 months ago
2007
IEEE
Interest in face recognition systems has increased significantly due to the emergence of significant commercial opportunities in surveillance and security applications. In this pa...
JMLR
2006
13 years 7 months ago
2006
The eigenvalues of the kernel matrix play an important role in a number of kernel methods, in particular, in kernel principal component analysis. It is well known that the eigenva...
ICIP
2008
IEEE
14 years 9 months ago
2008
IEEE
This paper proposes a robust video fingerprinting method based on 2-Dimensional Oriented Principal Component Analysis (2D-OPCA) of affine covariant regions. The goal of video fing...