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» Co-Tracking Using Semi-Supervised Support Vector Machines
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ICML
1998
IEEE
16 years 20 days ago
Feature Selection via Concave Minimization and Support Vector Machines
Computational comparison is made between two feature selection approaches for nding a separating plane that discriminates between two point sets in an n-dimensional feature space ...
Paul S. Bradley, Olvi L. Mangasarian
ICPR
2006
IEEE
16 years 29 days ago
Feature selection for linear support vector machines
Feature selection is attracted much interest from researchers in many fields such as pattern recognition and data mining. In this paper, a novel algorithm for feature selection is...
Zhizheng Liang, Tuo Zhao
UAI
2000
15 years 1 months ago
Variational Relevance Vector Machines
The Support Vector Machine (SVM) of Vapnik [9] has become widely established as one of the leading approaches to pattern recognition and machine learning. It expresses predictions...
Christopher M. Bishop, Michael E. Tipping
ICIP
2001
IEEE
16 years 1 months ago
Support vector machine learning for image retrieval
In this paper, a novel method of relevance feedback is presented based on Support Vector Machine learning in the content-based image retrieval system. A SVM classifier can be lear...
Lei Zhang, Fuzong Lin, Bo Zhang
ICPR
2000
IEEE
16 years 28 days ago
Data Condensation in Large Databases by Incremental Learning with Support Vector Machines
An algorithmfor data condensation using support vector machines (SVM's)is presented. The algorithm extracts datapoints lying close to the class boundaries,whichform a much re...
Pabitra Mitra, C. A. Murthy, Sankar K. Pal