18 search results - page 3 / 4 » Sparse Kernel SVMs via Cutting-Plane Training |
RECOMB
2005
Springer
14 years 8 months ago
2005
Springer
Background: Support Vector Machines (SVMs) ? using a variety of string kernels ? have been successfully applied to biological sequence classification problems. While SVMs achieve ...
ICANN
2007
Springer
13 years 11 months ago
2007
Springer
Abstract. Trained support vector machines (SVMs) have a slow runtime classification speed if the classification problem is noisy and the sample data set is large. Approximating the...
COLING
2008
13 years 9 months ago
2008
Data-driven learning based on shift reduce parsing algorithms has emerged dependency parsing and shown excellent performance to many Treebanks. In this paper, we investigate the e...
JMLR
2006
13 years 7 months ago
2006
While classical kernel-based learning algorithms are based on a single kernel, in practice it is often desirable to use multiple kernels. Lanckriet et al. (2004) considered conic ...
ICML
2007
IEEE
14 years 8 months ago
2007
IEEE
Although support vector machines (SVMs) for binary classification give rise to a decision rule that only relies on a subset of the training data points (support vectors), it will ...