204 search results - page 5 / 41 » Scaling the Kernel Function to Improve Performance of the Su... |
GFKL
2007
Springer
13 years 11 months ago
2007
Springer
In many classification applications, Support Vector Machines (SVMs) have proven to be highly performing and easy to handle classifiers with very good generalization abilities. Howe...
ICDM
2007
IEEE
13 years 9 months ago
2007
IEEE
An easily implementable mixed-integer algorithm is proposed that generates a nonlinear kernel support vector machine (SVM) classifier with reduced input space features. A single ...
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...
COLT
1999
Springer
14 years 5 days ago
1999
Springer
—Support vector (SV) machines are linear classifiers that use the maximum margin hyperplane in a feature space defined by a kernel function. Until recently, the only bounds on th...
IJCNN
2007
IEEE
14 years 2 months ago
2007
IEEE
Abstract— The optimal model parameters of a kernel machine are typically given by the solution of a convex optimisation problem with a single global optimum. Obtaining the best p...