28 search results - page 4 / 6 » Reproducing kernel Hilbert spaces for spike train analysis |
162
Voted
JMLR
2002
15 years 3 months ago
2002
A central problem in learning is selection of an appropriate model. This is typically done by estimating the unknown generalization errors of a set of models to be selected from a...
171
Voted
WACV
2012
IEEE
13 years 11 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...
109
Voted
ALT
2005
Springer
16 years 19 days ago
2005
Springer
Abstract. We propose an independence criterion based on the eigenspectrum of covariance operators in reproducing kernel Hilbert spaces (RKHSs), consisting of an empirical estimate ...
115
Voted
ICML
2009
IEEE
16 years 4 months ago
2009
IEEE
Similarity measures in many real applications generate indefinite similarity matrices. In this paper, we consider the problem of classification based on such indefinite similariti...
154
Voted
IJCAI
2007
15 years 5 months ago
2007
We propose a novel variant of the conjugate gradient algorithm, Kernel Conjugate Gradient (KCG), designed to speed up learning for kernel machines with differentiable loss functio...