Titlebook: Neural Information Processing; 24th International C Derong Liu,Shengli Xie,El-Sayed M. El-Alfy Conference proceedings 2017 Springer Interna

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Bayesian Curve Fitting Based on RBF Neural Networkss functions (RBF) neural network by adding an extra linear neuron and incorporating the Bayesian learning. The unknown function represented by datasets is approximated by a set of Gaussian basis functions with a linear term. The additional linear term offsets the localized behavior induced by basis

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Removing Bias from Diverse Data Clusters for Ensemble Classificationersify the data they are trained on. Sampling techniques such as bagging have been used for this task in the past, however we argue that since they maintain the global distribution, they do not engender diversity. We instead make a principled argument for the use of k-Means clustering to create dive

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An Efficient Algorithm for Complex-Valued Neural Networks Through Training Input Weightslearning machine (CELM) is an efficient algorithm, which owes faster convergence than the common complex backpropagation (CBP) neural networks. However, it needs more hidden neurons to reach competitive performance. Recently, an efficient learning algorithm is proposed for the single-hidden layer fe

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Lecture Notes in Computer Sciencehttp://image.papertrans.cn/n/image/663590.jpg

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Neural Information Processing978-3-319-70093-9Series ISSN 0302-9743 Series E-ISSN 1611-3349