53 search results - page 2 / 11 » Large Scale Transductive SVMs |
PKDD
2009
Springer
13 years 12 months ago
2009
Springer
We explore an algorithm for training SVMs with Kernels that can represent the learned rule using arbitrary basis vectors, not just the support vectors (SVs) from the training set. ...
CORR
2010
Springer
13 years 5 months ago
2010
Springer
In this paper we propose an approximated structured prediction framework for large scale graphical models and derive message-passing algorithms for learning their parameters effic...
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...
JMLR
2006
13 years 5 months ago
2006
Support vector machines are trained by solving constrained quadratic optimization problems. This is usually done with an iterative decomposition algorithm operating on a small wor...
NECO
2007
13 years 4 months ago
2007
Most literature on Support Vector Machines (SVMs) concentrate on the dual optimization problem. In this paper, we would like to point out that the primal problem can also be solve...