57 search results - page 2 / 12 » Adaptive Kernel Principal Component Analysis with Unsupervis... |
ICPR
2006
IEEE
2006
IEEE
Regularized Locality Preserving Learning of Pre-Image Problem in Kernel Principal Component Analysis
13 years 10 months ago
In this paper, we address the pre-image problem in kernel principal component analysis (KPCA). The preimage problem finds a pattern as the pre-image of a feature vector defined in...
ECCV
2004
Springer
14 years 6 months ago
2004
Springer
Abstract. We present a method for learning feature descriptors using multiple images, motivated by the problems of mobile robot navigation and localization. The technique uses the ...
ICML
2003
IEEE
14 years 5 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...
ICMCS
2006
IEEE
13 years 10 months ago
2006
IEEE
It is well-known that supervised learning techniques such as linear discriminant analysis (LDA) often suffer from the so called small sample size problem when apply to solve face ...
JMLR
2010
13 years 2 months ago
2010
A large number of learning algorithms, for example, spectral clustering, kernel Principal Components Analysis and many manifold methods are based on estimating eigenvalues and eig...