186 search results - page 1 / 38 » Sparse Kernel Regressors |
ICANN
2001
Springer
13 years 9 months ago
2001
Springer
Sparse kernel regressors have become popular by applying the support vector method to regression problems. Although this approach has been shown to exhibit excellent generalization...
ICANN
2007
Springer
13 years 11 months ago
2007
Springer
Abstract. In this paper we discuss sparse least squares support vector regressors (sparse LS SVRs) defined in the reduced empirical feature space, which is a subspace of mapped tr...
IDEAL
2004
Springer
13 years 10 months ago
2004
Springer
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...
ICANN
2005
Springer
13 years 10 months ago
2005
Springer
Sparse regression is the problem of selecting a parsimonious subset of all available regressors for an efficient prediction of a target variable. We consider a general setting in w...
ESANN
2008
13 years 6 months ago
2008
In our previous work, we have developed sparse least squares support vector regressors (sparse LS SVRs) trained in the primal form in the reduced empirical feature space. In this p...