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.
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Titolo: | Improved Neural Network for SVM Learning |
Autori: | |
Data di pubblicazione: | 2002 |
Rivista: | |
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. |
Handle: | http://hdl.handle.net/11567/208929 |
Appare nelle tipologie: | 01.01 - Articolo su rivista |
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