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• W84249390 abstract "Connectionist feed-forward networks, trained with back-propagation, can be used both for nonlinear regression and for (discrete one-of-C) classification, depending on the form of training. This report contains two papers on feed-forward networks. The papers can be read independently. They are intended for the theoretically-aware practitioner or algorithm-designer; however, they also contain a review and comparison of several learning theories so they provide a perspective for the theoretician. The first paper works through Bayesian methods to complement back-propagation in the training of feed-forward networks. The second paper addresses a problem raised by the first: how to efficiently calculate second derivatives on feed-forward networks." @default.
• W84249390 created "2016-06-24" @default.
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• W84249390 date "1991-07-05" @default.
• W84249390 modified "2023-09-24" @default.
• W84249390 title "Two papers on feed-forward networks" @default.
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• W84249390 hasPublicationYear "1991" @default.
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