Abstract
This paper discusses the application of Influence Diagrams on training Neural Networks. The basic concepts of these two methodologies are presented as a brief review. The conventional back-propagation training procedure is compared to other alternatives, by means of an example on visual pattern recognition.
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Davalo, E. & NaÏm, P. Des Réseaux de Neurones. Eurolles, Paris, 1990.
Henrion, Max, Breese, J. S. & Horvitz, E. Decision Analysis and Expert Systems. AI Magazine, Winter 91.
Hertz, Jonh A., Krogh, A. & Palmer, R. Introduction to the Theory of Neural Computation. Addison-Wesley, Redwood City, 1991.
Lauritzen, S. L. & Spiegelhalter, D. J. Local Computations with Probabilities on Graphical Structures and Their Application to Expert Systems. Journal Royal Statistical Society, 50, 1988.
Machado, A. C. & Campos, M. M. On The Application of Influence Diagrams to Pattern Recognition Problems. Proceedings of the Workshop on Cybernetic Vision, SÃo Carlos, 1994.
Pearl, J. Fusion, Propagation and Structuring in Belief Networks. Artificial Intelligence, 29, 1986.
Pearl, J. Distributed Revision of Composite Beliefs. Artificial Intelligence, 33, 1987.
Rumelhart, D., Hinton, G. & Williams R. Parallel Distributed Processing: Explorations in the Microstructures of Cognition. MIT Press, Cambridge, 1986.
Suermondt, H. J. & Cooper, G. F. Updating Probabilities in Multiply-Connected Belief Networks. Proceedings of the 4th Workshop on Uncertainty in Artificial Intelligence, Minneapolis, 1988.
Thomas, J. B. Introduction to Probability. Springer-Verlag, New York, 1986.
Tou, J. T. & Gonzalez, R. Pattern Recognition Principles. Reading, 1974.
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© 1995 Springer-Verlag Berlin Heidelberg
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Machado, A.M.C., Campos, M.F.M. (1995). Training neural networks with influence diagrams. In: Yao, X. (eds) Progress in Evolutionary Computation. EvoWorkshops EvoWorkshops 1993 1994. Lecture Notes in Computer Science, vol 956. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-60154-6_59
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DOI: https://doi.org/10.1007/3-540-60154-6_59
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