1. Y. Bengio and P. Frasconi. Credit assignment through time: Alternatives to backpropagation. In J. Cowan, G. Tesauro, and J. Alspector, editors, Advances in Neural Information Processing Systems, Volume 5. Morgan Kaufmann, pp. 75–82, 1994.
2. Y. Bengio, P. Simard, and P. Frasconi. Learning long-term dependencies with gradient descent is difficult. IEEE Transactions on Neural Networks, 5 (2): 157–166, 1994.
3. L. Blum, F. Chucker, M. Shub, and S. Smale. Complexity and Real Computation. Springer, 1998.
4. B. DasGupta, and B. Hammer. On approximate learning by multi-layered feedforward circuits. In: H. Arimura, S. Jain, A. Sharma (eds.), Algorithmic Learning Theory 2000, Springer, pp. 264–278, 2000.
5. M. W. Craven and J. W. Shavlik. Using sampling and queries to extract rules from trained neural networks. In: Proceedings of the Eleventh International Conference on Machine Learning, Morgan Kaufmann, pp. 37–45, 1994.