• 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