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Bibliography

1
H. B. Barlow, T. P. Kaushal, and G. J. Mitchison.
Finding minimum entropy codes.
Neural Computation, 1:412-423, 1989.

2
S. Becker.
Unsupervised learning procedures for neural networks.
International Journal of Neural Systems, 2(1 & 2):17-33, 1991.

3
F. Földiák.
Forming sparse representations by local anti-hebbian learning.
Biological Cybernetics, 64:165-170, 1990.

4
R. Linsker.
Self-organization in a perceptual network.
IEEE Computer, 21:105-117, 1988.

5
E. Oja.
Neural networks, principal components, and subspaces.
International Journal of Neural Systems, 1(1):61-68, 1989.

6
B. A. Pearlmutter and G. E. Hinton.
G-maximization: An unsupervised learning procedure for discovering regularities.
In J. S. Denker, editor, Neural Networks for Computing: American Institute of Physics Conference Proceedings 151, volume 2, pages 333-338, 1986.

7
D. Prelinger.
Diploma thesis, in preparation, 1992.
Institut für Informatik, Technische Universität München.

8
J. Rubner and K. Schulten.
Development of feature detectors by self-organization: A network model.
Biological Cybernetics, 62:193-199, 1990.

9
T. D. Sanger.
An optimality principle for unsupervised learning.
In D. S. Touretzky, editor, Advances in Neural Information Processing Systems 1, pages 11-19. San Mateo, CA: Morgan Kaufmann, 1989.

Schmidhuber:91predmin">10
J. H. Schmidhuber.
Learning factorial codes by predictability minimization.
Technical Report CU-CS-565-91, Dept. of Comp. Sci., University of Colorado at Boulder, December 1991.

Schmidhuber:92ncchunker">11
J. H. Schmidhuber.
Learning complex, extended sequences using the principle of history compression.
Neural Computation, 4(2): 1992.

Schmidhuber:92nips">12
J. H. Schmidhuber.
Learning unambiguous reduced sequence descriptions.
In J. E. Moody, S. J. Hanson, and R. P. Lippman, editors, Advances in Neural Information Processing Systems 4, to appear. San Mateo, CA: Morgan Kaufmann, 1992.

13
C. E. Shannon.
A mathematical theory of communication (part III).
Bell System Technical Journal, XXVII:623-656, 1948.

14
F. M. Silva and L. B. Almeida.
A distributed decorrelation algorithm.
In Erol Gelenbe, editor, Neural Networks, Advances and Applications. North-Holland, 1991.
To appear.

15
P. J. Werbos.
Beyond Regression: New Tools for Prediction and Analysis in the Behavioral Sciences.
PhD thesis, Harvard University, 1974.

16
R. S. Zemel and G. E. Hinton.
Discovering viewpoint-invariant relationships that characterize objects.
In D. S. Lippman, J. E. Moody, and D. S. Touretzky, editors, Advances in Neural Information Processing Systems 3, pages 299-305. San Mateo, CA: Morgan Kaufmann, 1991.



Juergen Schmidhuber 2003-02-13


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