955 search results - page 2 / 191 » Support Vector Neural Training |
ANNPR
2006
Springer
13 years 9 months ago
2006
Springer
Abstract. Decomposition techniques are used to speed up training support vector machines but for linear programming support vector machines (LP-SVMs) direct implementation of decom...
IJCNN
2008
IEEE
14 years 6 days ago
2008
IEEE
— We discuss sparse support vector machines (sparse SVMs) trained in the reduced empirical feature space. Namely, we select the linearly independent training data by the Cholesky...
ICANN
2005
Springer
13 years 11 months ago
2005
Springer
Abstract. Radial basis function (RBF) kernels are widely used for support vector machines. But for model selection, we need to optimize the kernel parameter and the margin paramete...
ICANN
2007
Springer
13 years 12 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...
IJCNN
2000
IEEE
13 years 10 months ago
2000
IEEE
The main purpose of this paper is to compare the support vector machine (SVM) developed by Vapnik with other techniques such as Backpropagation and Radial Basis Function (RBF) Net...