178 search results - page 19 / 36 » Extensions of Manifold Learning Algorithms in Kernel Feature... |
TCS
2008
13 years 7 months ago
2008
This paper studies a novel paradigm for learning formal languages from positive and negative examples which consists of mapping strings to an appropriate highdimensional feature s...
IJON
2002
13 years 7 months ago
2002
We study the relation between maps of a high-dimensional stimulus manifold onto an essentially two-dimensional cortical area and low-dimensional maps of stimulus features such as ...
ICMCS
2006
IEEE
14 years 1 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 ...
ICIP
2010
IEEE
13 years 5 months ago
2010
IEEE
Texture classification is a classical yet still active topic in computer vision and pattern recognition. Recently, several new texture classification approaches by modeling textur...
ICPR
2006
IEEE
2006
IEEE
Regularized Locality Preserving Learning of Pre-Image Problem in Kernel Principal Component Analysis
14 years 1 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...