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» Explicit recursivity into reproducing kernel Hilbert spaces
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ICML
2004
IEEE
15 years 10 months ago
Learning with non-positive kernels
In this paper we show that many kernel methods can be adapted to deal with indefinite kernels, that is, kernels which are not positive semidefinite. They do not satisfy Mercer...
Alexander J. Smola, Cheng Soon Ong, Stéphan...
ICML
2008
IEEE
15 years 10 months ago
An RKHS for multi-view learning and manifold co-regularization
Inspired by co-training, many multi-view semi-supervised kernel methods implement the following idea: find a function in each of multiple Reproducing Kernel Hilbert Spaces (RKHSs)...
Vikas Sindhwani, David S. Rosenberg
ALT
2005
Springer
15 years 6 months ago
Measuring Statistical Dependence with Hilbert-Schmidt Norms
Abstract. We propose an independence criterion based on the eigenspectrum of covariance operators in reproducing kernel Hilbert spaces (RKHSs), consisting of an empirical estimate ...
Arthur Gretton, Olivier Bousquet, Alex J. Smola, B...
IEICET
2010
101views more  IEICET 2010»
14 years 8 months ago
Irregular Sampling on Shift Invariant Spaces
Let V (φ) be a shift invariant subspace of L2 (R) generated by a Riesz or frame generator φ(t) in L2 (R). We assume that φ(t) is suitably chosen so that V (φ) becomes a reprod...
Kil Hyun Kwon, Jaekyu Lee
JMLR
2002
137views more  JMLR 2002»
14 years 9 months ago
The Subspace Information Criterion for Infinite Dimensional Hypothesis Spaces
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...
Masashi Sugiyama, Klaus-Robert Müller