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Möller and Thrun, 1990
Möller, K. and Thrun, S. (1990).
Task modularization by network modulation.
In Rault, J., editor, Proceedings of Neuro-Nimes '90, pages 419-432.

Pearlmutter, 1989
Pearlmutter, B. A. (1989).
Learning state space trajectories in recurrent neural networks.
Neural Computation, 1:263-269.

Robinson and Fallside, 1987
Robinson, A. J. and Fallside, F. (1987).
The utility driven dynamic error propagation network.
Technical Report CUED/F-INFENG/TR.1, Cambridge University Engineering Department.

Rumelhart et al., 1986
Rumelhart, D. E., Hinton, G. E., and Williams, R. J. (1986).
Learning internal representations by error propagation.
In Rumelhart, D. E. and McClelland, J. L., editors, Parallel Distributed Processing, volume 1, pages 318-362. MIT Press.

Schmidhuber, 1990a
Schmidhuber, J. H. (1990a).
Dynamische neuronale Netze und das fundamentale raumzeitliche Lernproblem. Dissertation, Institut für Informatik, Technische Universität München.

Schmidhuber, 1990b
Schmidhuber, J. H. (1990b).
Learning algorithms for networks with internal and external feedback.
In Touretzky, D. S., Elman, J. L., Sejnowski, T. J., and Hinton, G. E., editors, Proc. of the 1990 Connectionist Models Summer School, pages 52-61. San Mateo, CA: Morgan Kaufmann.

Schmidhuber, 1991a
Schmidhuber, J. H. (1991a).
Learning to generate sub-goals for action sequences.
In Simula, O., editor, Proceedings of the International Conference on Artificial Neural Networks ICANN 91, to appear. Elsevier Science Publishers B.V.

Schmidhuber, 1991b
Schmidhuber, J. H. (1991b).
An $O(n^3)$ learning algorithm for fully recurrent networks.
Technical Report FKI-151-91, Institut für Informatik, Technische Universität München.

v.d. Malsburg, 1981
v.d. Malsburg, C. (1981).
Internal Report 81-2, Abteilung für Neurobiologie, Max-Planck Institut für Biophysik und Chemie, Göttingen.

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

Williams and Zipser, 1989
Williams, R. J. and Zipser, D. (1989).
Experimental analysis of the real-time recurrent learning algorithm.
Connection Science, 1(1):87-111.

Juergen Schmidhuber 2003-02-13

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