MW-OBS: An improved pruning method for topology design of neural networks

Tsinghua Science and Technology

Volumn 11, Issue 3, 2006, Pages 307-312

  Zhu, Yan ^a   Lu, Yingrong ^b   Li, Qian ^a  

^a TSINGHUA UNIVERSITY   (China)

^b JILIN UNIVERSITY   (China)

Author keywords

Neural networks; Pruning method; Topology design of artificial neural network

Indexed keywords

ARTIFICIAL INTELLIGENCE; COMPUTER NETWORKS; ERRORS; JAVA PROGRAMMING LANGUAGE; LARGE SCALE SYSTEMS; STABILITY; STRUCTURES (BUILT OBJECTS); TOPOLOGY;

ARTIFICIAL NEURAL NETWORK; MULTIWEIGHT OPTIMAL BRAIN SURGEON; PRUNING METHOD; TOPOLOGY DESIGN;

NEURAL NETWORKS;

EID: 33747038693     PISSN: 10070214     EISSN: None     Source Type: Journal    
DOI: 10.1016/S1007-0214(06)70194-8     Document Type: Article

References (15)

1. Baum E, Haussler B D. What size net gives valid generalization? Neural Computation, 1989, 1: 151-160.
2. Frean M. The upstar algorithm: A method for constructing and training feed-forward neural networks. Neural Computation, 1990, 2: 198-209.
3. Ragg T, Braun H, Landsberg H. A comparative study of neural network optimization techniques. In: Proceedings of the International Conference on Artificial Neural Networks and Genetic Algorithm. New York: Springer Wien, 1997.
4. Zhu Y, Chen J. Studies on genetic multilayer feedforward neural networks and the development of GMNN. In: 1999 IEEE International Conference on Systems, Man, and Cybernetics. Tokyo, 1999: 401-406.
5. Zhu Y, Guo X T. Study on evolutionary neural networks and software development with Java. Chinese Journal of Mechanical Engineering, 2000, 13(Sup): 52-62. (in Chinese)
6. Zhu Y, Yu M. A kind of parallel evolutionary neural networks in distributed computation environments. In: ISSS. 46th. Shanghai, 2002.
7. Zhu Y, Zhang N. Study on parallel hybrid evolutionary algorithm and its application in RBF networks. In: SCI'2003. Orlando, 2003.
8. Li M Q, Xu B Y, Kou J S. On the combination of genetic algorithms and neural networks. System Engineering Theory and Practice, 1999, 19(2): 65-69.
9. Garcia-Pedrajas N, Hervas-Martinez C, Munoz-Perez J. COVNET: A cooperative coevolutionary model for evolving artificial neural networks. IEEE Transactions on Neural Networks, 2003, 14(3): 575-596.
10. Nikolay Y N, Hitoshi I. Learning polynomial feedforward neural networks by genetic programming and backpropagation. IEEE Transactions on Neural Networks, 2003, 14(2): 337-350.
11. Sexton R S, Dorsey R E, Sikander N A. Simultaneous optimization of neural network function and architecture algorithm. Decision Support Systems, 2004, 36: 283-296.
12. Hassibi B, Storck D G. Second order derivatives for network pruning: Optimal brain surgeon. In: Cowan J, Giles L, eds. Advances in Neural Information Processing Systems 5. San Mateo, CA: Morgan Kaufmann, 1993: 164-171.
13. Stahlberger A, Riedmiller M. Fast network prtming and feature extraction using the unit-OBS algorithm. In: Advances in Neural Information Processing Systems. Denver, 1996: 2-5.
14. Hassibi B, Storck D G, Wolff G J. Optimal brain surgeon and general network pruning. In: IEEE International Conference on Neural Networks. Anchorage, Alaska, 1993, 1: 293-299.
15. Stahlberger A, Riedmiller M. Fast network pruning and feature extraction by removing complete units. In: Mozer M C, Jordan M I, Petsch T, eds. Advances in Neural Information Processing Systems 9. Messachussets: MIT Press, 1997.