25 search results - page 2 / 5 » Training SVMs Without Offset |
MCS
2005
Springer
13 years 10 months ago
2005
Springer
Support Vector Machines (SVMs) have been successfully applied to solve a large number of classification and regression problems. However, SVMs suffer from the catastrophic forgetti...
ICPR
2008
IEEE
14 years 6 months ago
2008
IEEE
We present a new technique that employs support vector machines and Gaussian mixture densities to create a generative/discriminative joint classifier. In the past, several approac...
TNN
2008
13 years 5 months ago
2008
Hard-margin support vector machines (HM-SVMs) suffer from getting overfitting in the presence of noise. Soft-margin SVMs deal with this problem by introducing a regularization term...
SIGIR
2006
ACM
13 years 11 months ago
2006
ACM
Large scale learning is often realistic only in a semi-supervised setting where a small set of labeled examples is available together with a large collection of unlabeled data. In...
IJCNN
2008
IEEE
13 years 11 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...