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COLT
2005
Springer
14 years 1 months ago
Learning Convex Combinations of Continuously Parameterized Basic Kernels
We study the problem of learning a kernel which minimizes a regularization error functional such as that used in regularization networks or support vector machines. We consider thi...
Andreas Argyriou, Charles A. Micchelli, Massimilia...
ICA
2007
Springer
13 years 9 months ago
Gradient Convolution Kernel Compensation Applied to Surface Electromyograms
Abstract. This paper introduces gradient based method for robust assessment of the sparse pulse sources, such as motor unit innervation pulse trains in the filed of electromyograp...
Ales Holobar, Damjan Zazula
NECO
2000
190views more  NECO 2000»
13 years 7 months ago
Generalized Discriminant Analysis Using a Kernel Approach
We present a new method that we call Generalized Discriminant Analysis (GDA) to deal with nonlinear discriminant analysis using kernel function operator. The underlying theory is ...
G. Baudat, Fatiha Anouar
JMLR
2002
160views more  JMLR 2002»
13 years 7 months ago
Kernel Independent Component Analysis
We present a class of algorithms for independent component analysis (ICA) which use contrast functions based on canonical correlations in a reproducing kernel Hilbert space. On th...
Francis R. Bach, Michael I. Jordan
ICML
2009
IEEE
13 years 5 months ago
Multiple indefinite kernel learning with mixed norm regularization
We address the problem of learning classifiers using several kernel functions. On the contrary to many contributions in the field of learning from different sources of information...
Matthieu Kowalski, Marie Szafranski, Liva Ralaivol...