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26 April 2024
 
  » arxiv » 2010.00327

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A new upper bound for sampling numbers
Nicolas Nagel ; Martin Schäfer ; Tino Ullrich ;
Date 30 Sep 2020
AbstractWe provide a new upper bound for sampling numbers $(g_n)_{nin mathbb{N}}$ associated to the compact embedding of a separable reproducing kernel Hilbert space into the space of square integrable functions. There are universal constants $C,c>0$ (which are specified in the paper) such that $$
g^2_n leq frac{Clog(n)}{n}sumlimits_{kgeq lfloor cn floor} sigma_k^2quad,quad ngeq 2,, $$ where $(sigma_k)_{kin mathbb{N}}$ is the sequence of singular numbers (approximation numbers) of the Hilbert-Schmidt embedding $ ext{Id}:H(K) o L_2(D,varrho_D)$. The algorithm which realizes the bound is a least squares algorithm based on a specific set of sampling nodes. These are constructed out of a random draw in combination with a down-sampling procedure coming from the celebrated proof of Weaver’s conjecture, which was shown to be equivalent to the Kadison-Singer problem. Our result is non-constructive since we only show the existence of a linear sampling operator realizing the above bound. The general result can for instance be applied to the well-known situation of $H^s_{ ext{mix}}(mathbb{T}^d)$ in $L_2(mathbb{T}^d)$ with $s>1/2$. We obtain the asymptotic bound $$
g_n leq C_{s,d}n^{-s}log(n)^{(d-1)s+1/2},, $$ which improves on very recent results by shortening the gap between upper and lower bound to $sqrt{log(n)}$.
Source arXiv, 2010.00327
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