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» Support vector machine via nonlinear rescaling method
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ISCI
2008
165views more  ISCI 2008»
13 years 7 months ago
Support vector regression from simulation data and few experimental samples
This paper considers nonlinear modeling based on a limited amount of experimental data and a simulator built from prior knowledge. The problem of how to best incorporate the data ...
Gérard Bloch, Fabien Lauer, Guillaume Colin...
NECO
1998
151views more  NECO 1998»
13 years 7 months ago
Nonlinear Component Analysis as a Kernel Eigenvalue Problem
We describe a new method for performing a nonlinear form of Principal Component Analysis. By the use of integral operator kernel functions, we can e ciently compute principal comp...
Bernhard Schölkopf, Alex J. Smola, Klaus-Robe...
JMLR
2011
148views more  JMLR 2011»
13 years 2 months ago
Multitask Sparsity via Maximum Entropy Discrimination
A multitask learning framework is developed for discriminative classification and regression where multiple large-margin linear classifiers are estimated for different predictio...
Tony Jebara
ESANN
2004
13 years 8 months ago
Sparse LS-SVMs using additive regularization with a penalized validation criterion
This paper is based on a new way for determining the regularization trade-off in least squares support vector machines (LS-SVMs) via a mechanism of additive regularization which ha...
Kristiaan Pelckmans, Johan A. K. Suykens, Bart De ...
SDM
2010
SIAM
151views Data Mining» more  SDM 2010»
13 years 8 months ago
Fast Stochastic Frank-Wolfe Algorithms for Nonlinear SVMs
The high computational cost of nonlinear support vector machines has limited their usability for large-scale problems. We propose two novel stochastic algorithms to tackle this pr...
Hua Ouyang, Alexander Gray