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» Co-Tracking Using Semi-Supervised Support Vector Machines
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ICPR
2010
IEEE
13 years 8 months ago
Adaptive Incremental Learning with an Ensemble of Support Vector Machines
The incremental updating of classifiers implies that their internal parameter values can vary according to incoming data. As a result, in order to achieve high performance, incre...
Marcelo N. Kapp, Robert Sabourin, Patrick Maupin
MMS
2006
13 years 7 months ago
Support vector machine active learning for music retrieval
Searching and organizing growing digital music collections requires a computational model of music similarity. This paper describes a system for performing flexible music similarit...
Michael I. Mandel, Graham E. Poliner, Daniel P. W....
NIPS
2000
13 years 9 months ago
Active Support Vector Machine Classification
An active set strategy is applied to the dual of a simple reformulation of the standard quadratic program of a linear support vector machine. This application generates a fast new...
Olvi L. Mangasarian, David R. Musicant
BMCBI
2006
106views more  BMCBI 2006»
13 years 7 months ago
Prediction of the functional class of metal-binding proteins from sequence derived physicochemical properties by support vector
Metal-binding proteins play important roles in structural stability, signaling, regulation, transport, immune response, metabolism control, and metal homeostasis. Because of their...
H. H. Lin, L. Y. Han, H. L. Zhang, C. J. Zheng, B....
JMLR
2008
110views more  JMLR 2008»
13 years 7 months ago
Estimating the Confidence Interval for Prediction Errors of Support Vector Machine Classifiers
Support vector machine (SVM) is one of the most popular and promising classification algorithms. After a classification rule is constructed via the SVM, it is essential to evaluat...
Bo Jiang, Xuegong Zhang, Tianxi Cai