Title :
Neural network realization of support vector methods for pattern classification
Author :
Tan, Ying ; Xia, Youshen ; Wang, Jun
Author_Institution :
Dept. of Electron. Eng. & Inf. Sci., Univ. of Sci. & Technol. of China, Hefei, China
Abstract :
We apply a recurrent neural network to support vector machine (SVM) training for pattern recognition. Specifically, a primal-dual neural network is exploited to solve the quadratic programming problem encountered in training SVMs. The properties of the network allow one to design SVMs without adjustable network parameters and give a better solution for ill-posed problems
Keywords :
learning (artificial intelligence); pattern classification; quadratic programming; recurrent neural nets; learning; pattern classification; pattern recognition; quadratic programming; recurrent neural network; support vector machine; Automation; Error correction; Information science; Neural networks; Pattern classification; Pattern recognition; Quadratic programming; Recurrent neural networks; Support vector machine classification; Support vector machines;
Conference_Titel :
Neural Networks, 2000. IJCNN 2000, Proceedings of the IEEE-INNS-ENNS International Joint Conference on
Conference_Location :
Como
Print_ISBN :
0-7695-0619-4
DOI :
10.1109/IJCNN.2000.859430
