Preview
Unable to display preview. Download preview PDF.
References
Ruján P. and Marchand M. Complex Systems 3 (1989) 229–242
Ruján P. and Marchand M. Proceedings of IJCNN 1989, Washington Vol. II 105–110
Pellionisz, A. and LLinàs, R. Neuroscience 5 (1979) 1125–1136
Grötschel A. and Padberg, M. Polyhedral Theory in The Traveling Salesman Problem, Lenstra et al Eds, J. Wiley, 1986
Burnod, Y. and Korn, H. Proc. Natl. Acad. Sci. USA 86 (1989) 352–356
McCullogh W. S. and Pitts W. (1943) Bull. Math. Biophys. 5 115–133
M. L. Minsky, S. Papert: Perceptrons: An Introduction to Computational Geometry Cambridge Ma., MIT Press, 1969 and 1988
Rosenblatt, F. Psychoanalytic Review 65 (1958) 386
Rumelhart,D. E. and McClelland, J. L. (Eds) Parallel Distributed Processing Vol. 1–2, Cambridge Ma., Bradford Books, MIT Press, 1986
Mézard M. and Nadal J. P. J. Phys. A 22 (1989) 2191–2203
Marchand, M., Golea, M. and P. Ruján Europhys. Lett. 11 (1990) 487–492
Kinzel, W. and Opper, M. in Physics of Neural Networks, van Hemmen, Domany and Schulten (Eds) Spinger Verlag, 1989
Valiant L. G. Comm. of the ACM 27 pp. 1134–1142 (1984)
Fisher R. A. Contributions to Mathematical Statistics 32.179–32.188 John Wiley, New York, 1950
Widrow, B. Self-Organizing Systems 1962 Yovits et al (Eds) Spartan Books, Washington, D.C., 435–461 John Wiley, New York, 1950
Lambert, P. F. Methodologies of Pattern Recognition Watanabe M. S. (Ed.) 359–381 Academic Press, New York, 1969
Krauth, W. and Mézard M. J. Phys. A 20 (1987) L745
Opper M., Kinzel, W, Kleinz J. and Nehl, R. On the ability of the optimal Perceptron to generalize preprint Universität Gißen, February 1990
Anlauf J. K. and Biehl M. Europhys. Lett. 10 (1990) 687–692
D. E. Rumelhart, G. E. Hinton, R. J. Williams: Nature 323, 533–536 (1986)
Judd S. Proc. IEEE First Conference on Neural Networks San Diego 1987 Vol. II pp. 685–692 (IEEE Cat. No. 87TH0191-7)
Blum A. and Rivest R. Proc. of the 1988 Workshop on Computational Learning Theory pp. 9–18 Hussler D. and Pitt L. (Eds.) Morgan Kaufman, San Mateo, Ca.
Nadal J-P. Int. J. of Neural Sys. 1 (1989) 55
Golea M. and Marchand M. A growth algorithm for neural decision trees, submitted to Europhys. Lett.
Blumer A., Ehrenfeucht, A., Haussler, D. and Warmuth M. K. Inf. Proc. Lett. 24 (1987) 377–380
Knerr, S., Personnaz, L. and Dreyfus, G. to appear in Neurocomputing: Algorithms, Architectures and Applications NATO ASI Series, Springer Verlag 1990
Haussler, D., Littlestone, N. and Warmuth M. K. Predicting {0,1}-Functions on Randomly Drawn Points to be published
Lewis II P. M. and Coates C. L. Threshold Logic John Wiley & Sons, New York, 1967
Levin E., Tishby N. and Solla S. A. to appear in Proc. of the 1989 Workshop in Computational Learning Theory Györgyi G. and Tishby N. to be published
Saad D. and Marom E. Capacity expansion of neural network models using external coding, IJCNN 1989, Washington, D.C.
Gallant, S. L. Neural Networks. 3 (1990) 191–201
Poggio, T. A Parallel Vision Machine that Learns, in Models of Brain Function, Cotterill, R. Ed. Cambridge University Press, 1989
Dorn W. S. Quarterly of Applied Mathematics 18 (1960) 155–162
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 1990 Springer-Verlag
About this paper
Cite this paper
Ruján, P. (1990). Learning in multilayer networks: A geometric computational approach. In: Garrido, L. (eds) Statistical Mechanics of Neural Networks. Lecture Notes in Physics, vol 368. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3540532676_51
Download citation
DOI: https://doi.org/10.1007/3540532676_51
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-53267-5
Online ISBN: 978-3-540-46808-0
eBook Packages: Springer Book Archive