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Formalizing neural networks using graph transformations

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1997

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Fischer, Ingrid

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Proceedings of International Conference on Neural Networks (ICNN'97). IEEE, 1997, pp. 275-280. ISBN 0-7803-4122-8. Available under: doi: 10.1109/ICNN.1997.611678

Zusammenfassung

In this paper a unifying framework for the formalization of different types of neural networks and the corresponding algorithms for computation and training is presented. The used graph transformation system offers a formalism to verify properties of the networks and their algorithms. In addition the presented methodology can be used as a tool to visualize and design different types of networks along with all required algorithms. An algorithm that adapts network parameters using standard gradient descent as well as parts of a constructive, topology-changing algorithm for probabilistic neural networks are used to demonstrate the proposed formalism.

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International Conference on Neural Networks (ICNN'97), Houston, TX, USA
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ISO 690BERTHOLD, Michael R., Ingrid FISCHER, 1997. Formalizing neural networks using graph transformations. International Conference on Neural Networks (ICNN'97). Houston, TX, USA. In: Proceedings of International Conference on Neural Networks (ICNN'97). IEEE, 1997, pp. 275-280. ISBN 0-7803-4122-8. Available under: doi: 10.1109/ICNN.1997.611678
BibTex
@inproceedings{Berthold1997Forma-24285,
  year={1997},
  doi={10.1109/ICNN.1997.611678},
  title={Formalizing neural networks using graph transformations},
  isbn={0-7803-4122-8},
  publisher={IEEE},
  booktitle={Proceedings of International Conference on Neural Networks (ICNN'97)},
  pages={275--280},
  author={Berthold, Michael R. and Fischer, Ingrid}
}
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