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ICASSP
2008
IEEE
14 years 2 months ago
Learning the kernel via convex optimization
The performance of a kernel-based learning algorithm depends very much on the choice of the kernel. Recently, much attention has been paid to the problem of learning the kernel it...
Seung-Jean Kim, Argyrios Zymnis, Alessandro Magnan...
NIPS
2003
13 years 9 months ago
Learning to Find Pre-Images
We consider the problem of reconstructing patterns from a feature map. Learning algorithms using kernels to operate in a reproducing kernel Hilbert space (RKHS) express their solu...
Gökhan H. Bakir, Jason Weston, Bernhard Sch&o...
IJON
2006
119views more  IJON 2006»
13 years 8 months ago
Support vector machine for functional data classification
Abstract. Functional data analysis is a growing research field and numerous works present a generalization of the classical statistical methods to function classification or regres...
Fabrice Rossi, Nathalie Villa
IDEAL
2004
Springer
14 years 1 months ago
Orthogonal Least Square with Boosting for Regression
A novel technique is presented to construct sparse regression models based on the orthogonal least square method with boosting. This technique tunes the mean vector and diagonal c...
Sheng Chen, Xunxian Wang, David J. Brown
CSSC
2008
84views more  CSSC 2008»
13 years 8 months ago
Nonparametric Regression as an Example of Model Choice
Nonparametric regression can be considered as a problem of model choice. In this paper we present the results of a simulation study in which several nonparametric regression techn...
Laurie Davies, Ursula Gather, Henrike Weinert