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Titlebook: Computational Learning Theory; Third European Confe Shai Ben-David Conference proceedings 1997 Springer-Verlag Berlin Heidelberg 1997 Algor

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Zielsetzung und Problemstellung, and their generalization to split hypergraphs (for which we give a split-finding algorithm) when the boundary region has constant radius greater than 1. We use a notion of indistinguishability of concepts that is appropriate for this model.
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Progress in Colloid and Polymer Sciencenerate boxes (that is, boxes that depend only on .(1) variables) in time poly(., log ℓ) (generalizing the learnability of .(1)-DNF and of boxes in .(1) dimensions). The algorithm for this class uses only equivalence queries and it can also be used to learn the class of unions of .(1) boxes (from equivalence queries only).
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Learning boxes in high dimension,nerate boxes (that is, boxes that depend only on .(1) variables) in time poly(., log ℓ) (generalizing the learnability of .(1)-DNF and of boxes in .(1) dimensions). The algorithm for this class uses only equivalence queries and it can also be used to learn the class of unions of .(1) boxes (from equivalence queries only).
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Learning from incomplete boundary queries using split graphs and hypergraphs, and their generalization to split hypergraphs (for which we give a split-finding algorithm) when the boundary region has constant radius greater than 1. We use a notion of indistinguishability of concepts that is appropriate for this model.
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