Title :
Penalty OBS scheme for feedforward neural network
Author_Institution :
Dept. of Autom. Control, North Univ. of China
Abstract :
This paper presented a new scheme called penalty OBS (optimal brain surgeon) for the feedforward neural network learning. The penalty OBS scheme takes OBS pruning case as a penalty item of the network cost function, and develops two applied methods based on the common algorithms of network learning. As a novel revision of OBS, the new scheme not only saves the runtime to calculate Hessian matrix after training, but also improves the generalization a lot and keeps over-linear rapidity of convergence. The simulating results verified the advantages
Keywords :
Hessian matrices; feedforward neural nets; learning (artificial intelligence); Hessian matrix; feedforward neural network learning; network cost function; optimal brain surgeon pruning; overlinear convergence rapidity; penalty optimal brain surgeon scheme; Artificial intelligence; Biological neural networks; Computational modeling; Convergence; Cost function; Feedforward neural networks; Neural networks; Runtime; Surges; Taylor series;
Conference_Titel :
Tools with Artificial Intelligence, 2005. ICTAI 05. 17th IEEE International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
0-7695-2488-5
DOI :
10.1109/ICTAI.2005.93