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ML
2002
ACM
107views Machine Learning» more  ML 2002»
13 years 7 months ago
Training Invariant Support Vector Machines
Practical experience has shown that in order to obtain the best possible performance, prior knowledge about invariances of a classification problem at hand ought to be incorporated...
Dennis DeCoste, Bernhard Schölkopf
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 20 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. ...