57 search results - page 5 / 12 » Adaptive Kernel Principal Component Analysis with Unsupervis... |
ICDM
2003
IEEE
14 years 22 days ago
2003
IEEE
We study the use of kernel subspace methods for learning low-dimensional representations for classification. We propose a kernel pooled local discriminant subspace method and com...
ECML
2004
Springer
14 years 25 days ago
2004
Springer
This work presents a novel procedure for computing (1) distances between nodes of a weighted, undirected, graph, called the Euclidean Commute Time Distance (ECTD), and (2) a subspa...
ICPR
2006
IEEE
14 years 8 months ago
2006
IEEE
This paper presents a novel alternative approach, namely weakly supervised learning (WSL), to learn the pre-image of a feature vector in the feature space induced by a kernel. It ...
SYNASC
2007
IEEE
14 years 1 months ago
2007
IEEE
In recent years several models have been proposed for text categorization. Within this, one of the widely applied models is the vector space model (VSM), where independence betwee...
JMLR
2006
13 years 7 months ago
2006
Kernels are two-placed functions that can be interpreted as inner products in some Hilbert space. It is this property which makes kernels predestinated to carry linear models of l...