Fast Second Order Learning Algorithm for Feedforward Multilayer Neural Networks and its Applications

Author:

Osowski Stanislaw,Bojarczak Piotr,Stodolski Maciej

Publisher

Elsevier BV

Subject

Artificial Intelligence,Cognitive Neuroscience

Reference18 articles.

1. Achenie, L.E. (1994). Computational experience with a quasi Newton method based training of the feedforward neural networks. Proc. World Congress on Neural Networks, San Diego, III607–III612.

2. First and second order methods for learning: between steepest descent and Newton methods;Battiti;Neural Computation,1992

3. Battiti, R., & Masulli, F. (1990). BFGS optimization for faster and automated supervised learning. Proc. IEEE Int. NN Conf., Paris (pp. 757–760).

4. Conjugate gradient algorithm for efficient training of artificial neural networks;Charalambous;IEEE Proc. G.,1992

5. Initializing back propagation with prototypes;Denoeux;Neural Networks,1993

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