773 search results - page 2 / 155 » Kernel Change-point Analysis |
ESANN
2003
13 years 6 months ago
2003
Abstract. We focus on covariance criteria for finding a suitable subspace for regression in a reproducing kernel Hilbert space: kernel principal component analysis, kernel partial...
ICML
2006
IEEE
14 years 6 months ago
2006
IEEE
In Kernel Fisher discriminant analysis (KFDA), we carry out Fisher linear discriminant analysis in a high dimensional feature space defined implicitly by a kernel. The performance...
WACV
2012
IEEE
12 years 1 months ago
2012
IEEE
A convenient way of analysing Riemannian manifolds is to embed them in Euclidean spaces, with the embedding typically obtained by flattening the manifold via tangent spaces. This...
GPB
2010
13 years 2 months ago
2010
The detection of genes that show similar profiles under different experimental conditions is often an initial step in inferring the biological significance of such genes. Visualiz...
ICCV
2009
IEEE
13 years 3 months ago
2009
IEEE
The use of Mercer kernel methods in statistical learning theory provides for strong learning capabilities, as seen in kernel principal component analysis and support vector machin...