Semilinear Predictability Minimization Produces Well-Known Feature Detectors

Neural Computation

Volumn 8, Issue 4, 1996, Pages 773-786

  Schmidhuber, Jürgen ^a   Eldracher, Martin ^a   Foltin, Bernhard ^b  

^a DALLE MOLLE INSTITUTE FOR ARTIFICIAL INTELLIGENCE IDSIA   (Switzerland)

^b TECHNICAL UNIVERSITY OF MUNICH   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 0039238512     PISSN: 08997667     EISSN: None     Source Type: Journal    
DOI: 10.1162/neco.1996.8.4.773     Document Type: Article

References (17)

1. Atick, J. J., Li, Z., and Redlich, A. N. 1992. Understanding retinal color coding from first principles. Neural Comp. 4, 559-572.
2. Barlow, H. B., Kaushal, T. P., and Mitchison, G. J. 1989. Finding minimum entropy codes. Neural Comp. 1(3), 412-423.
3. Barrow, H. G. 1987. Learning receptive fields. Proc. IEEE 1st Annu. Conf. Neural Networks IV, 115-121.
4. Deco, G., and Obradovic, L. 1996. An Information-Theoretic Approach to Neural Computing. Springer, NY.
5. Field, D. J. 1994. What is the goal of sensory coding? Neural Comp., 6, 559-601.
6. Fôldiák, P. 1990. Forming sparse representations by local anti-Hebbian learning. Biol. Cybern. 64, 165-170.
7. Lindstädt, S. 1993. Comparison of two unsupervised neural network models for redundancy reduction. In Proceedings of the 1993 Connectionist Models Summer School, M. C. Mozer, P. Smolensky, D. S. Touretzky, J. L. Elman, and A. S. Weigend, eds., pp. 308-315. Erlbaum Associates, Hillsdale, NJ.
8. Linsker, R. 1986a. From basic network principles to neural architecture: Emergence of orientation-selective cells. Proc. Natl. Acad. Sci. U.S.A. 83, 8779-8783.
9. Linsker, R. 1986b. From basic network principles to neural architecture: Emergence of spatial-opponent cells. Proc. Natl. Acad. Sci. U.S.A. 83, 8390-8394.
10. Linsker, R. 1988. Self-organization in a perceptual network. IEEE Comput. 21, 105-117.
11. MacKay, D. J. C., and Miller, K. D. 1990. Analysis of Linsker's simulation of Hebbian rules. Neural Comp. 2, 173-187.
12. Miller, K. D. 1994. A model for the development of simple cell receptive fields and the ordered arrangement of orientation columns through activity-dependent competition between on- and off-center inputs. J. Neurosci. 14(1), 409-441.
13. Rubner, J., and Schulten, K. 1990. Development of feature detectors by self-organization: A network model. Biol. Cybern. 62, 193-199.
14. Rubner, J., and Tavan, P. 1989. A self-organization network for principal-component analysis. Europhys. Lett. 10, 693-698.
15. Schmidhuber, J. H. 1992. Learning factorial codes by predictability minimization. Neural Comp. 4(6), 863-879.
16. Schmidhuber, J. H. 1993. Netzwerkarchitekturen, Zielfunktionen und Kettenregel. Habilitationsschrift, Institut für Informatik, Technische Universität München.
17. Schmidhuber, J. H. 1994. Neural predictors for detecting and removing redundant information. In Adaptive Behavior and Learning, H. Cruse, J. Dean, and H. Ritter, eds., number 9, pp. 135-145. Center for Interdisciplinary Research, Universität Bielefeld.