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Showing papers on "Statistical learning theory published in 1962"


Book ChapterDOI
01 Jan 1962
TL;DR: The same approach may be useful in combining purposes, using the machine to learn more about the behavior of living organisms and the principles of learning theory to extend the capabilities of the machine.
Abstract: Probabilistic formulations have been used to design both mathematical models for the behavior of living organisms and machines which display some of the properties of living organisms. Examples of the former include the statistical learning theory of Estes (1950) and the stochastic learning model of Bush and Mosteller (1951). Examples of the latter include the conditional probability machines of Uttley (1956) and the Perceptron of Rosenblatt (1958). Additional references may be found in the reviews by Estes (1959), Gilstrap and Lee (1960), and Minsky (1961). Since these uses of the probabilistic approach apply to either purpose individually, the same approach may be useful in combining purposes, using the machine to learn more about the behavior of living organisms and the principles of learning theory to extend the capabilities of the machine.

4 citations