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Related papers: Universal discretization

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Discretization of the uniform norm of functions from a given finite dimensional subspace of continuous functions is studied. We pay special attention to the case of trigonometric polynomials with frequencies from an arbitrary finite set…

Numerical Analysis · Mathematics 2021-12-14 Boris Kashin , Sergei Konyagin , Vladimir Temlyakov

The problem of replacing an integral norm with respect to a given probability measure by the corresponding integral norm with respect to a discrete measure is discussed in the paper. The above problem is studied for elements of finite…

Numerical Analysis · Mathematics 2019-11-01 F. Dai , A. Prymak , V. N. Temlyakov , S. Tikhonov

Discretization of the uniform norm of functions from a given finite dimensional subspace of continuous functions is studied. Previous known results show that for any $N$-dimensional subspace of the space of continuous functions it is…

Functional Analysis · Mathematics 2024-05-08 E. D. Kosov , V. N. Temlyakov

The paper is devoted to discretization of integral norms of functions from a given finite dimensional subspace. This problem is very important in applications but there is no systematic study of it. We present here a new technique, which…

Numerical Analysis · Mathematics 2017-03-13 V. N. Temlyakov

The main goal of this paper is to provide a brief survey of recent results which connect together results from different areas of research. It is well known that numerical integration of functions with mixed smoothness is closely related to…

Numerical Analysis · Mathematics 2018-12-12 Vladimir Temlyakov

This survey addresses sampling discretization and its connections with other areas of mathematics. The survey concentrates on sampling discretization of norms of elements of finite-dimensional subspaces. We present here known results on…

Functional Analysis · Mathematics 2022-02-11 B. Kashin , E. Kosov , I. Limonova , V. Temlyakov

This paper surveys recent developments in the sampling discretization of integral and uniform norms for functions in general finite-dimensional spaces. These results generalize the classical Marcinkiewicz-Zygmund inequalities for…

Numerical Analysis · Mathematics 2026-03-04 F. Dai , E. Kosov , V. Temlyakov

It is proved that the Fibonacci and the Frolov point sets, which are known to be very good for numerical integration, have optimal rate of decay of dispersion with respect to the cardinality of sets. This implies that the Fibonacci and the…

Numerical Analysis · Mathematics 2017-10-05 V. N. Temlyakov

The paper is devoted to discretization of integral norms of functions from a given finite dimensional subspace. We use recent general results on sampling discretization to derive a new Marcinkiewicz type discretization theorem for the…

Numerical Analysis · Mathematics 2020-05-14 Vladimir Temlyakov

A set $Q$ in $\mathbb{Z}_+^d$ is a lower set if $(k_1,\dots,k_d)\in Q$ implies $(l_1,\dots,l_d)\in Q$ whenever $0\le l_i\le k_i$ for all $i$. We derive new and refine known results regarding the cardinality of the lower sets of size $n$ in…

Numerical Analysis · Mathematics 2025-04-15 F. Dai , A. Prymak , A. Shadrin , V. Temlyakov , S. Tikhonov

The paper addresses the problem of sampling discretization of integral norms of elements of finite-dimensional subspaces satisfying some conditions. We prove sampling discretization results under two standard kinds of assumptions --…

Numerical Analysis · Mathematics 2021-09-21 F. Dai , V. Temlyakov

Let $X_N$ be an $N$-dimensional subspace of $L_2$ functions on a probability space $(\Omega, \mu)$ spanned by a uniformly bounded Riesz basis $\Phi_N$. Given an integer $1\leq v\leq N$ and an exponent $1\leq q\leq 2$, we obtain universal…

Functional Analysis · Mathematics 2021-07-27 Feng Dai , V. Temlyakov

For the multivariate trigonometric polynomials we study convolution with the corresponding the de la Vallee Poussin kernel from the point of view of discretization. In other words, we replace the normalized Lebesgue measure by a discrete…

Numerical Analysis · Mathematics 2022-01-04 V. N. Temlyakov

The paper addresses a problem of sampling discretization of integral norms of elements of finite-dimensional subspaces satisfying some conditions. We prove sampling discretization results under a standard assumption formulated in terms of…

Functional Analysis · Mathematics 2023-04-13 F. Dai , E. Kosov , V. Temlyakov

Recently, it was discovered that for a given function class $\mathbf{F}$ the error of best linear recovery in the square norm can be bounded above by the Kolmogorov width of $\mathbf{F}$ in the uniform norm. That analysis is based on deep…

Numerical Analysis · Mathematics 2023-05-17 F. Dai , V. Temlyakov

We study the concept of universal sets from the additive--combinatorial point of view. Among other results we obtain some applications of this type of uniformity to sets avoiding solutions to linear equations, and get an optimal upper bound…

Combinatorics · Mathematics 2024-04-03 Ilya D. Shkredov

Constructing a discretization of a given set is a major problem in various theoretical and applied disciplines. An offset discretization of a set $X$ is obtained by taking the integer points inside a closed neighborhood of $X$ of a certain…

Discrete Mathematics · Computer Science 2018-08-10 Boris Brimkov , Valentin E. Brimkov

The paper is devoted to discretization of integral norms of functions from a given finite dimensional subspace. Even though this problem is extremely important in applications, its systematic study has begun recently. In this paper we…

Classical Analysis and ODEs · Mathematics 2020-01-28 F. Dai , A. Prymak , A. Shadrin , V. Temlyakov , S. Tikhonov

The new ingredient of this paper is that we consider infinitely dimensional classes of functions and instead of the relative error setting, which was used in previous papers on norm discretization, we consider the absolute error setting. We…

Numerical Analysis · Mathematics 2018-12-20 Vladimir Temlyakov

$D$-optimal designs originate in statistics literature as an approach for optimal experimental designs. In numerical analysis points and weights resulting from maximal determinants turned out to be useful for quadrature and interpolation.…

Numerical Analysis · Mathematics 2024-12-04 Felix Bartel , Lutz Kämmerer , Kateryna Pozharska , Martin Schäfer , Tino Ullrich
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