17 search results - page 1 / 4 » Large scale semi-supervised linear SVMs |
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...
KDD
2008
ACM
14 years 5 months ago
2008
ACM
Efficient training of direct multi-class formulations of linear Support Vector Machines is very useful in applications such as text classification with a huge number examples as w...
NIPS
2001
13 years 6 months ago
2001
Support Vector Machines (SVMs) are currently the state-of-the-art models for many classication problems but they suer from the complexity of their training algorithm which is at l...
KDD
2006
ACM
14 years 5 months ago
2006
ACM
Linear Support Vector Machines (SVMs) have become one of the most prominent machine learning techniques for highdimensional sparse data commonly encountered in applications like t...
ECML
2006
Springer
13 years 7 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...