23 search results - page 1 / 5 » Coordinate Descent Method for Large-scale L2-loss Linear Sup... |
JMLR
2008
13 years 7 months ago
2008
Linear support vector machines (SVM) are useful for classifying large-scale sparse data. Problems with sparse features are common in applications such as document classification a...
ICML
2008
IEEE
14 years 8 months ago
2008
IEEE
In many applications, data appear with a huge number of instances as well as features. Linear Support Vector Machines (SVM) is one of the most popular tools to deal with such larg...
ICML
2008
IEEE
14 years 8 months ago
2008
IEEE
We show how the regularizer of Transductive Support Vector Machines (TSVM) can be trained by stochastic gradient descent for linear models and multi-layer architectures. The resul...
ECML
2006
Springer
13 years 9 months ago
2006
Springer
This paper presents a decomposition method for efficiently constructing 1-norm Support Vector Machines (SVMs). The decomposition algorithm introduced in this paper possesses many d...
TNN
2008
13 years 7 months ago
2008
Abstract--Large-margin methods, such as support vector machines (SVMs), have been very successful in classification problems. Recently, maximum margin discriminant analysis (MMDA) ...