406 search results - page 4 / 82 » Covering Numbers for Support Vector Machines |
IJCNN
2008
IEEE
14 years 4 months 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...
ICPR
2006
IEEE
14 years 11 months ago
2006
IEEE
We propose a classification method based on a decision tree whose nodes consist of linear Support Vector Machines (SVMs). Each node defines a decision hyperplane that classifies p...
ICANN
2001
Springer
14 years 2 months ago
2001
Springer
Empirical evidence indicates that the training time for the support vector machine (SVM) scales to the square of the number of training data points. In this paper, we introduce the...
ML
2002
ACM
13 years 9 months ago
2002
ACM
The problem of automatically tuning multiple parameters for pattern recognition Support Vector Machines (SVMs) is considered. This is done by minimizing some estimates of the gener...
ICONIP
2007
13 years 11 months ago
2007
In this paper we eliminate the need for parameter estimation associated with the set covering machine (SCM) by directly minimizing generalization error bounds. Firstly, we consider...