A psychologist who coauthored the 1986 account of learning internal representations by backpropagation. The method adjusts connection weights in a multilayer artificial neural network using how those weights contribute to an output error. It explains how hidden units can acquire useful representations rather than requiring every intermediate feature to be specified by hand.[ref]
Learning representations by back-propagating errors by David E. Rumelhart and others. 1986, abstract and pp. 533–536
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