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Abstract: The Theory of Computational Complexity can be used as guideline to design artificial neural networks. As an application, a class of polynomial architectures (architectures whose training can be accomplished in polynomial time) is found. This class, the m-(dlog 2 se) architectures, is defined from restrictions on networks (pyramidal architectures) whose learning process is proved to be NP-complete. Such an identification is based on a formal analysis, not on ad hoc experiments. Therefore,... (Update)
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BibTeX entry: (Update)
@misc{ souto-loading,
author = "Marcílio C.P. de Souto and Wilson R. de Oliveira",
title = "The Loading Problem for Pyramidal Neural Networks",
url = "citeseer.ist.psu.edu/427980.html" }
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