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IEEE Transactions on Neural Networks, 1993
This paper introduces techniques to train feedforward nets to automate ranking and classification tasks. The techniques are denoted mimic nets since the nets can always mimic self-consistent training data. The mimic nets are constructed not for any neurological analogy, but for computational ease and purposeful utility.
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This paper introduces techniques to train feedforward nets to automate ranking and classification tasks. The techniques are denoted mimic nets since the nets can always mimic self-consistent training data. The mimic nets are constructed not for any neurological analogy, but for computational ease and purposeful utility.
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Acta Informatica, 1995
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
U. Montanari, ROSSI, FRANCESCA
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zbMATH Open Web Interface contents unavailable due to conflicting licenses.
U. Montanari, ROSSI, FRANCESCA
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A Fast Learning Algorithm for Deep Belief Nets
Neural Computation, 2006Geoffrey E. Hinton +2 more
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An introduction to computing with neural nets
IEEE ASSP Magazine, 1987R. Lippmann
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Metabolic stability and epigenesis in randomly constructed genetic nets.
Journal of Theoretical Biology, 1969S. Kauffman, S. Kauffman
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The Application of Petri Nets to Workflow Management
J. Circuits Syst. Comput., 1998Wil M.P. van der Aalst
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