On the rate of convergence of greedy algorithms
Numerical Analysis
2023-04-14 v1 Numerical Analysis
Functional Analysis
Abstract
We prove some results on the rate of convergence of greedy algorithms, which provide expansions. We consider both the case of Hilbert spaces and the more general case of Banach spaces. The new ingredient of the paper is that we bound the error of approximation by the product of both norms -- the norm of and the -norm of . Typically, only the -norm of is used. In particular, we establish that some greedy algorithms (Pure Greedy Algorithm (PGA) and its generalizations) are as good as the Orthogonal Greedy Algorithm (OGA) in this new sense of the rate of convergence, while it is known that the PGA is much worth than the OGA in the standard sense.
Keywords
Cite
@article{arxiv.2304.06423,
title = {On the rate of convergence of greedy algorithms},
author = {V. N. Temlyakov},
journal= {arXiv preprint arXiv:2304.06423},
year = {2023}
}