English

Greedy Algorithms and Kolmogorov Widths in Banach Spaces

Functional Analysis 2019-08-06 v2

Abstract

Let XX be a Banach space and K\mathcal{K} be a compact subset in XX. We consider a greedy algorithm for finding an nn-dimensional subspace VnXV_n\subset X which can be used to approximate the elements of K\mathcal{K}. We are interested in how well the space VnV_n approximates the elements of K\mathcal{K}. For this purpose we compare the performance of greedy algorithm measured by σn(K)X:=dist(K,Vn)X\sigma_n(\mathcal{K})_X:=\text{dist}(\mathcal{K},V_n)_X with the Kolmogorov width dn(K)Xd_n(\mathcal{K})_X which is the best possible error one can achieve when approximating K\mathcal{K} by nn-dimensional subspaces. Various results in this direction have been given, e.g., in Binev et al. (SIAM J. Math. Anal. (2011)), DeVore et al. (Constr. Approx. (2013)) and Wojtaszczyk (J. Math. Anal. Appl. (2015)). The purpose of the present paper is to continue this line. We shall show that there exists a constant C>0C>0 such that σn(K)XCns+μ(log(n+2))min(s,1/2), n1, \sigma_n(\mathcal{K})_X\leq C n^{-s+\mu}\big(\log(n+2)\big)^{\min(s,1/2)}, \quad \ n\geq 1\,, if Kolmogorov widths dn(K)Xd_n(\mathcal{K})_X decay as nsn^{-s} and the Banach-Mazur distance between an arbitrary nn-dimensional subspace VnXV_n \subset X and 2n\ell_2^n satisfies d(Vn,2n)C1nμd(V_n,\ell_2^n)\leq C_1 n^\mu. In particular, when some additional information about the set K\mathcal{K} is given then there is no logarithmic factor in this estimate.

Keywords

Cite

@article{arxiv.1804.03935,
  title  = {Greedy Algorithms and Kolmogorov Widths in Banach Spaces},
  author = {Van Kien Nguyen},
  journal= {arXiv preprint arXiv:1804.03935},
  year   = {2019}
}

Comments

14 pages

R2 v1 2026-06-23T01:20:22.448Z