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Titlebook: Artificial Neural Networks - ICANN 2006; 16th International C Stefanos D. Kollias,Andreas Stafylopatis,Erkki Oja Conference proceedings 200

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Analytic Equivalence of Bayes a Posteriori Distributionson matrices and different learning performance from regular statistical models. In this paper, we prove mathematically that the learning coefficient is determined by the analytic equivalence class of Kullback information, and show experimentally that the stochastic complexity by the MCMC method is a
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Neural Network Architecture Selection: Size Depends on Function Complexityneralization process on the complexity of the function implemented by neural architecture is studied using a recently introduced measure for the complexity of the Boolean functions. Furthermore an association rule discovery (ARD) technique was used to find associations among subsets of items in the
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A Variational Formulation for the Multilayer Perceptronation, the learning problem for the multilayer perceptron lies in terms of finding a function which is an extremal for some functional. As we will see, a variational formulation for the multilayer perceptron provides a direct method for the solution of general variational problems, in any dimension
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