Some Complexity Results for Perceptron Networks (1998)
by
Barbara Hammer
| Venue: | International Conference on Artificial Neural Networks'98 |
| Citations: | 7 - 3 self |
BibTeX
@INPROCEEDINGS{Hammer98somecomplexity,
author = {Barbara Hammer},
title = {Some Complexity Results for Perceptron Networks},
booktitle = {International Conference on Artificial Neural Networks'98},
year = {1998},
pages = {639--644},
publisher = {Springer}
}
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Abstract
The loading problem is the problem to decide if a neural architecture can map a training set correctly with an appropriate choice of the weights.
Citations
| 214 | Learning long-term dependencies with gradient descent is difficult - Bengio, Simard, et al. - 1994 |
| 186 | Training a 3-node neural networks is np-complete - Blum, Rivest - 1992 |
| 88 | A Theory of Learning and Generalization - Vidyasagar - 1997 |
| 38 | On the complexity of polyhedral separability - Megiddo - 1988 |
| 35 | A new algorithm to find a point in every cell defined by a family of polynomials - Basu, Pollack, et al. - 1998 |
| 23 | On the complexity of training neural networks with continuous activation - DasGupta, Siegelmann, et al. - 1995 |
| 7 | Back-propagation is not efficient - Sima - 1996 |
| 5 | Training a sigmoidal network is difficult - Hammer - 1998 |
| 4 | Komplexitat neuronaler Lernprobleme - Schmitt - 1996 |
