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Function values are, in some sense, "almost as good" as general linear information for $L_2$-approximation (optimal recovery, data assimilation) of functions from a reproducing kernel Hilbert space. This was recently proved by new upper…

Numerical Analysis · Mathematics 2022-03-23 Aicke Hinrichs , David Krieg , Erich Novak , Jan Vybiral

We find two-sided estimates for Kolmogorov, Bernstein, linear and projection widths of the classes of convolutions of $2\pi$-periodic functions $\varphi$, such that $\|\varphi\|_2\le1$, with fixed generated kernels $\Psi_{\bar{\beta}}$,…

Classical Analysis and ODEs · Mathematics 2023-04-11 A. S. Serdyuk , I. V. Sokolenko

Our main interest in this paper is to study some approximation problems for classes of functions with mixed smoothness. We use technique, based on a combination of results from hyperbolic cross approximation, which were obtained in 1980s --…

Numerical Analysis · Mathematics 2016-02-17 Vladimir Temlyakov

Sampling recovery on some function classes is studied in this paper. Typically, function classes are defined by imposing smoothness conditions. It was understood in nonlinear approximation that structural conditions in the form of control…

Numerical Analysis · Mathematics 2024-06-27 V. Temlyakov

The article examines Nikolskii and Besov spaces with norms defined using "$L_p$-averaged" mixed moduli of continuity for functions of appropriate orders, instead of mixed moduli of continuity of known orders for certain mixed derivative…

Classical Analysis and ODEs · Mathematics 2024-01-19 S. N. Kudryavtsev

It is well-known that the problem of sampling recovery in the $L_2$-norm on unweighted Korobov spaces (Sobolev spaces with mixed smoothness) as well as classical smoothness classes such as H\"older classes suffers from the curse of…

Numerical Analysis · Mathematics 2024-02-26 David Krieg

Recent findings by Jahn, T. Ullrich, Voigtlaender [10] relate non-linear sampling numbers for the square norm to quantities involving trigonometric best $m-$term approximation errors in the uniform norm. Here we establish new results for…

Numerical Analysis · Mathematics 2024-07-24 Moritz Moeller , Serhii Stasyuk , Tino Ullrich

We consider the approximate recovery of multivariate periodic functions from a discrete set of function values taken on a rank-$s$ integration lattice. The main result is the fact that any (non-)linear reconstruction algorithm taking…

Numerical Analysis · Mathematics 2016-08-02 Glenn Byrenheid , Lutz Kämmerer , Tino Ullrich , Toni Volkmer

We obtain exact lower bounds for Kolmogorov $n$-widths in spaces $C$ and $L$ of classes of convolutions with Neumann kernel $N_{q,\beta}(t)=\sum\limits_{k=1}^{\infty}\dfrac{q^k}{k}\cos\left(kt-\dfrac{\beta\pi}{2}\right)$, ${q\in(0,1)}$,…

Classical Analysis and ODEs · Mathematics 2013-12-24 V. V. Bodenchuk

This article offers a comprehensive treatment of polynomial functional regression, culminating in the establishment of a novel finite sample bound. This bound encompasses various aspects, including general smoothness conditions, capacity…

Numerical Analysis · Mathematics 2024-05-08 Markus Holzleitner , Sergei Pereverzyev

Lower and upper bounds are explored for the uniform (Kolmogorov) and $L^2$-distances between the distributions of weighted sums of dependent summands and the normal law. The results are illustrated for several classes of random variables…

Probability · Mathematics 2023-08-08 S. G. Bobkov , G. P. Chistyakov , F. Götze

In this article, we obtain the order estimates for the Kolmogorov widths of sets with conditions on the norm in the weighted Sobolev space $W^r_{p_1}$ and in the weighted space $L_{p_0}$.

Functional Analysis · Mathematics 2022-06-22 A. A. Vasil'eva

Solutions of numerous equations of mathematical physics such as elliptic, weakly singular, singular, hypersingular integral equations belong to functional classes $\bar Q^u_{r \gamma}(\Omega,1)$ and $Q^u_{r \gamma}(\Omega,1)$ defined over…

Numerical Analysis · Mathematics 2013-03-05 Ilya V. Boykov

We study volumes of sections of convex origin-symmetric bodies in $\mathbb{R}% ^{n}$ induced by orthonormal systems on probability spaces. The approach is based on volume estimates of \ John-L\"{o}wner ellipsoids and expectations of norms…

Functional Analysis · Mathematics 2022-12-08 Alexander Kushpel

This paper develops fundamental limits of deep neural network learning by characterizing what is possible if no constraints are imposed on the learning algorithm and on the amount of training data. Concretely, we consider Kolmogorov-optimal…

Machine Learning · Computer Science 2021-03-15 Dennis Elbrächter , Dmytro Perekrestenko , Philipp Grohs , Helmut Bölcskei

In this paper, we consider the problem of reconstructing piecewise smooth functions to high accuracy from nonuniform samples of their Fourier transform. We use the framework of nonuniform generalized sampling (NUGS) to do this, and to…

Numerical Analysis · Mathematics 2014-10-02 Ben Adcock , Milana Gataric , Anders C. Hansen

We consider the problem of approximating a function in general nonlinear subsets of $L^2$ when only a weighted Monte Carlo estimate of the $L^2$-norm can be computed. Of particular interest in this setting is the concept of sample…

Numerical Analysis · Mathematics 2021-08-12 Philipp Trunschke

We determine lower and exact estimates of Kolmogorov, Gelfand and linear $n$-widths of unit balls in Sobolev norms in $L_{p}$-spaces on compact Riemannian manifolds. As it was shown by us previously these lower estimates are exact…

Classical Analysis and ODEs · Mathematics 2015-09-16 Isaac Z. Pesenson

We prove that $d_n(W^1_1,L_q)\asymp n^{-1/2}\log n$, $2<q<\infty$. This completes the study of orders of decay of Kolmogorov widths for the classical case of the univariate Sobolev classes of integer smoothness.

Functional Analysis · Mathematics 2025-02-11 Yuri Malykhin

In this paper, we obtain order estimates for the Kolmogorov widths of periodic Sobolev classes with restictions on derivatives of order $r_j$ with respect to $j$th variable in metrics $L_{p_j}$ ($1\le j\le d$).

Functional Analysis · Mathematics 2024-02-20 A. A. Vasil'eva