155 search results - page 3 / 31 » Sparse support vector machines trained in the reduced empiri... |
ALT
2001
Springer
14 years 3 months ago
2001
Springer
This paper concerns the design of a Support Vector Machine (SVM) appropriate for the learning of Boolean functions. This is motivated by the need of a more sophisticated algorithm ...
KDD
2006
ACM
14 years 6 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...
ICMCS
2006
IEEE
14 years 8 days ago
2006
IEEE
In this paper an effective method of using SVM classifier for multiple feature classification is proposed. Compared with traditional combination methods where all needed base clas...
ICML
2004
IEEE
14 years 7 months ago
2004
IEEE
Learning general functional dependencies is one of the main goals in machine learning. Recent progress in kernel-based methods has focused on designing flexible and powerful input...
PR
2006
13 years 6 months ago
2006
In many pattern recognition applications, high-dimensional feature vectors impose a high computational cost as well as the risk of "overfitting". Feature Selection addre...