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Unlabeled Compression Schemes for Maximum Classes

Authors: Dima Kuzmin; Manfred K. Warmuth;

Unlabeled Compression Schemes for Maximum Classes

Abstract

Maximum concept classes of VC dimension d over n domain points have size n C ≤d, and this is an upper bound on the size of any concept class of VC dimension d over n points. We give a compression scheme for any maximum class that represents each concept by a subset of up to d unlabeled domain points and has the property that for any sample of a concept in the class, the representative of exactly one of the concepts consistent with the sample is a subset of the domain of the sample. This allows us to compress any sample of a concept in the class to a subset of up to d unlabeled sample points such that this subset represents a concept consistent with the entire original sample. Unlike the previously known compression scheme for maximum classes (Floyd and Warmuth, 1995) which compresses to labeled subsets of the sample of size equal d, our new scheme is tight in the sense that the number of possible unlabeled compression sets of size at most d equals the number of concepts in the class.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
3
Average
Top 10%
Average
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