The recurrent network of Xia et al. was proposed for solving quadratic programming problems and was recently adapted to support vector machine (SVM) learning by Tan et al.We show that this formulation contains some unnecessary circuit which, furthermore, can fail to provide the correct value of one of the SVM parameters and suggest how to avoid these drawbacks.

Improved Neural Network for SVM Learning

ANGUITA, DAVIDE;
2002

Abstract

The recurrent network of Xia et al. was proposed for solving quadratic programming problems and was recently adapted to support vector machine (SVM) learning by Tan et al.We show that this formulation contains some unnecessary circuit which, furthermore, can fail to provide the correct value of one of the SVM parameters and suggest how to avoid these drawbacks.
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11567/208929
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 46
  • ???jsp.display-item.citation.isi??? 40
social impact