25 search results - page 2 / 5 » Training SVMs Without Offset |
MCS
2005
Springer
15 years 3 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
15 years 10 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...
108
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TNN
2008
14 years 9 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...
85
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SIGIR
2006
ACM
15 years 3 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...
103
Voted
IJCNN
2008
IEEE
15 years 3 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...