Feed-forward neural networks trained with back-propagation, or a variation of it, constitute the most widely applied of all synthetic neural network paradigms. Several efforts have been (directed towards faster training of such networks. Most of these efforts attempt to take as large isteps as possible during the training process. However, another potential source of inefficiency
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