187 search results - page 3 / 38 » Nonlinear Component Analysis as a Kernel Eigenvalue Problem |
ICML
2003
IEEE
14 years 7 months ago
2003
IEEE
In this paper, we address the problem of finding the pre-image of a feature vector in the feature space induced by a kernel. This is of central importance in some kernel applicatio...
PR
2007
13 years 5 months ago
2007
Feature extraction is among the most important problems in face recognition systems. In this paper, we propose an enhanced kernel discriminant analysis (KDA) algorithm called kern...
COLT
2004
Springer
13 years 11 months ago
2004
Springer
The main goal of this paper is to prove inequalities on the reconstruction error for Kernel Principal Component Analysis. With respect to previous work on this topic, our contribu...
WACV
2008
IEEE
14 years 19 days ago
2008
IEEE
In recent years, many researchers are studying object categorization problem. It is reported that bag of keypoints approach which is based on local features without topological in...
NIPS
2008
13 years 7 months ago
2008
Kernel Principal Component Analysis (KPCA) is a popular generalization of linear PCA that allows non-linear feature extraction. In KPCA, data in the input space is mapped to highe...