Titlebook: Computational Learning Theory; 4th European Confere Paul Fischer,Hans Ulrich Simon Conference proceedings 1999 Springer-Verlag Berlin Heide

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Second-Order-Faktorenanalyse (SFA)d size that approximately minimizes the proportion of misclassified examples in a training set, even if there is a network that correctly classifies all of the training examples. In particular, for a training set that is correctly classified by some two-layer linear threshold network with . hidden u

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Thomas Zumbroich,Andreas Mülleres alone and a . sized decision tree representation of the function constructed, in polynomial time. In contrast, such a function cannot be exactly learned with equivalence queries alone using general decision trees and other representation classes as hypotheses..Our results imply others which may b

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Das Verfahren der Gew?sserstrukturkartierungressions, where every term in the consequent of every clause appears also in the antecedent of the clause, is learnable. The result holds both for the model where interpretations are examples (learning from interpretations) and the model where clauses are examples (learning from entailment)..The pap

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,Umsetzung des Entwurfs in Prim?rcode,Such algorithms use roughly .(..) weights which can be prohibitively expensive. Surprisingly, algorithms like Winnow require only . weights (one per variable) and the mistake bound of these algorithms is not too much worse than the mistake bound of the more costly algorithms. The purpose of this pap