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
Link To Document :
بازگشت