109 search results - page 6 / 22 » Using Kernel Basis with Relevance Vector Machine for Feature... |
ICPR
2002
IEEE
14 years 9 months ago
2002
IEEE
In this paper we address two aspects related to the exploitation of Support Vector Machines (SVM) for classification in real application domains, such as the detection of objects ...
ICASSP
2011
IEEE
13 years 9 days ago
2011
IEEE
This paper presents a sound source (talker) localization method using only a single microphone. In our previous work [1], we discussed the single-channel sound source localization...
COLT
1999
Springer
14 years 25 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...
ICML
2004
IEEE
14 years 9 months ago
2004
IEEE
Text categorization algorithms usually represent documents as bags of words and consequently have to deal with huge numbers of features. Most previous studies found that the major...
IJCNN
2008
IEEE
14 years 3 months ago
2008
IEEE
— We propose a feature selection criterion based on kernel discriminant analysis (KDA) for an -class problem, which finds eigenvectors on which the projected class data are loca...