Competitive learning by information maximization: Eliminating dead neurons in competitive learning

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 2714, Issue , 2003, Pages 99-106

  Kamimura, Ryotaro ^a  

^a TOKAI UNIVERSITY   (Japan)

Author keywords

Competitive learning; Dead neurons; Mutual information maximization; Winner take all

Indexed keywords

INFORMATION THEORY; NEURONS; STEREO VISION;

CLASSIFICATION PERFORMANCE; COMPETITIVE LEARNING; DEAD NEURONS; INFORMATION MAXIMIZATION; MUTUAL INFORMATION MAXIMIZATION; MUTUAL INFORMATIONS; ROAD CLASSIFICATIONS; WINNER TAKE ALLS;

NEURAL NETWORKS;

EID: 34047229946     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/3-540-44989-2_13     Document Type: Article

References (13)

1. R. Linsker, "Self-organization in a perceptual network," Computer, vol. 21, pp. 105-117, 1988.
2. R. Linsker, "How to generate ordered maps by maximizing the mutual information between input and output," Neural Computation, vol. 1, pp. 402-411, 1989.
3. R. Kamimura and S. Nakanishi, "Hidden information maximization for feature detection and rule discovery," Network, vol. 6, pp. 577-622, 1995.
4. R. Kamimura and S. Nakanishi, "Improving generalization performance by information minimization," IEICE Transactions on Information and Systems, vol. E78-D, no. 2, pp. 163-173, 1995:
5. G. Deco, W. Finnof, and H. G. Zimmermann, "Unsupervised mutual information criterion for elimination of overtraining in supervised multiplayer networks," Neural Computation, vol. 7, pp. 86-107, 1995.
6. Y. Akiyama and T. Furuya, "An extension of the back-propagation learning which performs entropy maximization as well as error minimization," Tech. Rep. NC91-6, IEICE Technical Report, 1991.
7. R. Kamimura, T. Kamimura, and T. R. Shultz, "Information theoretic competitive learning and linguistic rule acquistion," Transactions of the Japanese Society for Artificial Intelligence, vol. 16, no. 2, pp. 287-298, 2001.
8. R. Kamimura, T. Kamimura, and O. Uchida, "Flexible feature discovery and structural information," Connection Science, vol. 13, no. 4, pp. 323-347, 2001.
9. D. DeSieno, "Adding a conscience to competitive learning," in Proceedings of IEEE International Conference on Neural Networks, (San Diego), pp. 117-124, IEEE, 1988.
10. S. C. Ahalt, A. K. Krishnamurthy, P. Chen, and D. E. Melton, "Competitive learning algorithms for vector quantization," Neural Networks, vol. 3, pp. 277-290, 1990.
11. L. Xu, "Rival penalized competitive learning for clustering analysis, RBF net, and curve detection," IEEE Transaction on Neural Networks, vol. 4, no. 4, pp. 636-649, 1993.
12. A. Luk and S. Lien, "Properties of the generalized lotto-type competitive learning," in Proceedings of International conference on neural information processing, (San Mateo: CA), pp. 1180-1185, Morgan Kaufmann Publishers, 2000.
13. M. Marc and M. V. Hulle, Faithful representations and topographic maps. New York: John Wiley and Sons, Inc, 2000.