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In Valiant (1984) 'learning' was formalized as the process of estimating a Boolean function (or a related 'concept') in a certain class from randomly generated samples of the portion of its graph where the function has value 1.
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New York, Las Vergnas, Lecture Notes, Computational Learning Theory, David Haussler, Symbolic Computation, Annals of Statistics, First Workshop, Guedes de Oliveira, Hilbert Mechanization Theorem, North York, Santa Cruz, Theory of Matroids, Andrzej Ehrenfeucht, Convergence of Stochastic Processes, Invariant Theoretic Methods, Michael Kearns, Peaucellier's Linkage, Special Issue, Stage of Geometry Theorem-Proving, The University of Texas
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