Title :
Effective neural network training with a different learning rate for each weight
Author :
Magoulas, G.D. ; Plagianakos, Vassilis P. ; Vrahatis, M.N.
Author_Institution :
Dept. of Inf., Athens Univ., Greece
Abstract :
Batch training algorithms with a different learning rate for each weight are investigated. The adaptive learning rate algorithms of this class that apply inexact one-dimensional subminimization are analyzed and their global convergence is studied. Simulations are conducted to evaluate the convergence behavior of two training algorithms of this class and to compare them with several popular training methods
Keywords :
adaptive systems; convergence; learning (artificial intelligence); minimisation; neural nets; adaptive learning rate algorithms; batch training algorithms; different learning rate; error function minimization; global convergence; inexact one-dimensional subminimization; neural network training; simulations; weighting; Artificial neural networks; Convergence; Neural networks; Nonlinear equations; Tires;
Conference_Titel :
Electronics, Circuits and Systems, 1999. Proceedings of ICECS '99. The 6th IEEE International Conference on
Conference_Location :
Pafos
Print_ISBN :
0-7803-5682-9
DOI :
10.1109/ICECS.1999.812354
