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ICML
1998
IEEE
14 years 8 months 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
ICASSP
2009
IEEE
14 years 2 months ago
Combining VTS model compensation and support vector machines
It is difficult to adapt discriminative classifiers, particularly kernel based ones such as support vector machines (SVMs), to handle mismatches between the training and test da...
Mark J. F. Gales, Federico Flego
BIBE
2008
IEEE
150views Bioinformatics» more  BIBE 2008»
13 years 8 months ago
Automatic DNA microarray gridding based on Support Vector Machines
This paper presents a novel method for DNA microarray gridding based on Support Vector Machine (SVM) classifiers. It employs a set of soft-margin SVMs to estimate the lines of the ...
Dimitris G. Bariamis, Dimitris Maroulis, Dimitrios...
NECO
1998
83views more  NECO 1998»
13 years 7 months ago
Properties of Support Vector Machines
Support Vector Machines (SVMs) perform pattern recognition between two point classes by nding a decision surface determined by certain points of the training set, termed Support V...
Massimiliano Pontil, Alessandro Verri
ISMIR
2005
Springer
166views Music» more  ISMIR 2005»
14 years 1 months ago
Song-Level Features and Support Vector Machines for Music Classification
Searching and organizing growing digital music collections requires automatic classification of music. This paper describes a new system, tested on the task of artist identifica...
Michael I. Mandel, Dan Ellis