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JMLR
2008
123views more  JMLR 2008»
13 years 7 months ago
Optimization Techniques for Semi-Supervised Support Vector Machines
Due to its wide applicability, the problem of semi-supervised classification is attracting increasing attention in machine learning. Semi-Supervised Support Vector Machines (S3VMs...
Olivier Chapelle, Vikas Sindhwani, S. Sathiya Keer...
NN
2000
Springer
161views Neural Networks» more  NN 2000»
13 years 7 months ago
How good are support vector machines?
Support vector (SV) machines are useful tools to classify populations characterized by abrupt decreases in density functions. At least for one class of Gaussian data model the SV ...
Sarunas Raudys
ICML
2004
IEEE
14 years 8 months ago
Support vector machine learning for interdependent and structured output spaces
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...
Ioannis Tsochantaridis, Thomas Hofmann, Thorsten J...
ICML
2000
IEEE
14 years 8 months ago
Less is More: Active Learning with Support Vector Machines
We describe a simple active learning heuristic which greatly enhances the generalization behavior of support vector machines (SVMs) on several practical document classification ta...
Greg Schohn, David Cohn
EUROMICRO
2003
IEEE
14 years 21 days ago
Color Texture Recognition in Video Sequences using Wavelet Covariance Features and Support Vector Machines
This paper pertains to the recognition of textural regions for color video analysis. The proposed scheme uses the covariance of 2nd -order statistics on the wavelet domain, betwee...
Dimitrios K. Iakovidis, Dimitrios E. Maroulis, S. ...