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On the size of convex hulls of small sets

Mendelson, Shahar


We investigate two different notions of "size" which appear naturally in Statistical Learning Theory. We present quantitative estimates on the fat-shattering dimension and on the covering numbers of convex hulls of sets of functions, given the necessary data on the original sets. The proofs we present are relatively simple since they do not require extensive background in convex geometry.

CollectionsANU Research Publications
Date published: 2001-10
Type: Journal article
Source: Journal of Machine Learning Research


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