A Close Look to Margin Complexity and Related Parameters

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Michael Kallweit, Hans Ulrich Simon ;
Proceedings of the 24th Annual Conference on Learning Theory, PMLR 19:437-456, 2011.

Abstract

Concept classes can canonically be represented by sign-matrices,i.e., by matrices with entries 1 and -1. The question whethera sign-matrix (concept class) A can be learned by a machine that performs large margin classification is closely related to the“margin complexity” associated with A. We consider severalvariants of margin complexity, reveal how they are relatedto each other, and we reveal how they are related to other notions of learning-theoretic relevance like SQ-dimension, CSQ-dimension,and the Forster bound.

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