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Article overview
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A new upper bound for sampling numbers | Nicolas Nagel
; Martin Schäfer
; Tino Ullrich
; | Date: |
30 Sep 2020 | Abstract: | We 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 | Services: | Forum | Review | PDF | Favorites |
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