DocumentCode
2329142
Title
Support vector classifiers via gradient systems with discontinuous righthand sides
Author
Ferreira, Leonardo V. ; Kaszkurewicz, Eugenius ; Bhaya, Amit
Author_Institution
Dept. of Electr. Eng., Federal Univ. of Rio de Janeiro, Brazil
Volume
4
fYear
2004
fDate
25-29 July 2004
Firstpage
2997
Abstract
This paper implements support vector machines (SVM) for the discrimination of nonseparable classes using gradient systems with discontinuous righthand sides. The gradient systems are obtained from an exact penalty method applied to the constrained quadratic optimization problems. Global convergence to the solution of the corresponding constrained problems is shown to be independent of the penalty parameters and of the regularization parameter of the SVM.
Keywords
convergence; gradient methods; optimisation; support vector machines; constrained quadratic optimization problems; discontinuous righthand sides; exact penalty method; global convergence; gradient systems; support vector machines; Constraint optimization; Electronic mail; Least squares methods; Lyapunov method; Machine learning; Neural networks; Optimization methods; Recurrent neural networks; Support vector machine classification; Support vector machines;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 2004. Proceedings. 2004 IEEE International Joint Conference on
ISSN
1098-7576
Print_ISBN
0-7803-8359-1
Type
conf
DOI
10.1109/IJCNN.2004.1381144
Filename
1381144
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