Article ID Journal Published Year Pages File Type
420016 Discrete Applied Mathematics 2007 13 Pages PDF
Abstract

Covering numbers of precompact symmetric convex subsets of Hilbert spaces are investigated. Lower bounds are derived for sets containing orthogonal subsets with norms of their elements converging to zero sufficiently slowly. When these sets are convex hulls of sets with power-type covering numbers, the bounds are tight. The arguments exploit properties of generalized Hadamard matrices. The results are illustrated by examples from machine learning, neurocomputing, and nonlinear approximation.

Related Topics
Physical Sciences and Engineering Computer Science Computational Theory and Mathematics
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