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Proving Properties of Neural Networks with Graph Transformations

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1998

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Fischer, Ingrid
Koch, Manuel

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1998 IEEE International Joint Conference on Neural Networks Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98CH36227). IEEE, 1998, pp. 441-446. ISBN 0-7803-4859-1. Available under: doi: 10.1109/IJCNN.1998.682307

Zusammenfassung

Graph transformations offer a unifying framework to formalize neural networks together with their corresponding training algorithms. It is straightforward to describe also topology changing training algorithms with the help of these transformations. One of the benefits using this formal framework is the support for proving properties of the training algorithms. A training algorithm for probabilistic neural networks is used as an example to prove its termination and correctness on the basis of the corresponding graph rewriting rules.

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ICNN '98 - International Conference on Neural Networks, Anchorage, AK, USA
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ISO 690FISCHER, Ingrid, Manuel KOCH, Michael R. BERTHOLD, 1998. Proving Properties of Neural Networks with Graph Transformations. ICNN '98 - International Conference on Neural Networks. Anchorage, AK, USA. In: 1998 IEEE International Joint Conference on Neural Networks Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98CH36227). IEEE, 1998, pp. 441-446. ISBN 0-7803-4859-1. Available under: doi: 10.1109/IJCNN.1998.682307
BibTex
@inproceedings{Fischer1998Provi-24291,
  year={1998},
  doi={10.1109/IJCNN.1998.682307},
  title={Proving Properties of Neural Networks with Graph Transformations},
  isbn={0-7803-4859-1},
  publisher={IEEE},
  booktitle={1998 IEEE International Joint Conference on Neural Networks Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98CH36227)},
  pages={441--446},
  author={Fischer, Ingrid and Koch, Manuel and Berthold, Michael R.}
}
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