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Related papers: On best constants in $L^2$ approximation

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We establish L^p bounds on L^2 normalized spectral clusters for self-adjoint elliptic Dirichlet forms with Lipschitz coefficients. In two dimensions we obtain best possible bounds for all p between $2 and infinity, up to logarithmic losses…

Analysis of PDEs · Mathematics 2012-07-11 Herbert Koch , Hart Smith , Daniel Tataru

While it is well known that nonlinear methods of approximation can often perform dramatically better than linear methods, there are still questions on how to measure the optimal performance possible for such methods. This paper studies…

Numerical Analysis · Mathematics 2020-09-22 Albert Cohen , Ronald DeVore , Guergana Petrova , Przemyslaw Wojtaszczyk

We consider divergence-based high order discretizations of an $L^2$-based first order system least squares formulation of a second order elliptic equation with Robin boundary conditions. For smooth geometries, we show optimal convergence…

Numerical Analysis · Mathematics 2024-08-08 Maximilian Bernkopf , Jens Markus Melenk

We undertake a detailed study of the $L^2$ discrepancy of rational and irrational 2-dimensional lattices either with or without symmetrization. We give a full characterization of lattices with optimal $L^2$ discrepancy in terms of the…

Number Theory · Mathematics 2024-10-10 Bence Borda

Given a function $u\in L^2=L^2(D,\mu)$, where $D\subset \mathbb R^d$ and $\mu$ is a measure on $D$, and a linear subspace $V_n\subset L^2$ of dimension $n$, we show that near-best approximation of $u$ in $V_n$ can be computed from a…

Numerical Analysis · Mathematics 2021-09-14 Albert Cohen , Matthieu Dolbeault

We study the optimal rectangular-discrepancy approximation of permutons by finite permutations. We transfer bounds from discrepancy theory to this more restricted setup. Moreover, we show that superlinear approximation can occur only for…

Combinatorics · Mathematics 2026-05-05 Balázs Maga

We show several variants of concentration inequalities on the sphere stated as subgaussian estimates with optimal constants. For a Lipschitz function, we give one-sided and two-sided bounds for deviation from the median as well as from the…

Probability · Mathematics 2026-04-02 Guillaume Aubrun , Justin Jenkinson , Stanislaw J. Szarek

In this paper we provide a priori error estimates with explicit constants for both the $L^2$-projection and the Ritz projection onto spline spaces of arbitrary smoothness defined on arbitrary grids. This extends the results recently…

Numerical Analysis · Mathematics 2020-02-06 Espen Sande , Carla Manni , Hendrik Speleers

This short note presents a linear algebraic approach to proving dimension lower bounds for linear methods that solve $L^2$ function approximation problems. The basic argument has appeared in the literature before (e.g., Barron, 1993) for…

Machine Learning · Computer Science 2025-08-20 Daniel Hsu

The aim of this paper is to obtain convergence in mean in the uniform topology of piecewise linear approximations of Stochastic Differential Equations (SDEs) with $C^1$ drift and $C^2$ diffusion coefficients with uniformly bounded…

Probability · Mathematics 2025-03-13 Sahani Pathiraja

We develop almost-orthogonality principles for maximal functions associated with averages over line segments and directional singular integrals. Using them, we obtain sharp $L^2$-bounds for these maximal functions when the underlying…

Classical Analysis and ODEs · Mathematics 2025-10-13 Jongchon Kim

We develop an asymptotic theory for $L^2$ norms of sample mean vectors of high-dimensional data. An invariance principle for the $L^2$ norms is derived under conditions that involve a delicate interplay between the dimension $p$, the sample…

Statistics Theory · Mathematics 2015-03-13 Mengyu Xu , Danna Zhang , Wei Biao Wu

We compute the optimal constant and characterise the maximisers at all spatial scales for the Agmon--H\"ormander $L^2$-Fourier adjoint restriction estimate on the sphere. The maximisers switch back and forth from being constants to being…

Classical Analysis and ODEs · Mathematics 2022-03-14 Giuseppe Negro , Diogo Oliveira e Silva

We study the space complexity of sketching cuts and Laplacian quadratic forms of graphs. We show that any data structure which approximately stores the sizes of all cuts in an undirected graph on $n$ vertices up to a $1+\epsilon$ error must…

Data Structures and Algorithms · Computer Science 2018-01-01 Charles Carlson , Alexandra Kolla , Nikhil Srivastava , Luca Trevisan

Through reducing the problem to rational orthogonal system (Takenaka-Malmquist system), this note gives a proof for existence of n-best rational approximation to functions in the Hardy H2(D) space by using pseudohyperbolic distance.

Functional Analysis · Mathematics 2021-10-27 Tao Qian , Yan-Bo Wang

We study the optimal approximation of the solution of an operator equation by certain n-term approximations with respect to specific classes of frames. We study worst case errors and the optimal order of convergence and define suitable…

Numerical Analysis · Mathematics 2007-05-23 Stephan Dahlke , Erich Novak , Winfried Sickel

In this paper, we specify a set of optimal subspaces for $L_2$ approximation of three classes of functions in the Sobolev space $W^{(r)}_2$, defined on a segment and subject to certain boundary conditions. All of these subspaces are…

Classical Analysis and ODEs · Mathematics 2019-05-28 A. Yu. Ulitskaya , O. L. Vinogradov

This note has a twofold purpose. To improve the best known lower estimates of the Hardy-Littlewood inequality for $m$-linear forms in $\ell_{p}$ spaces and to provide a closed formula encompassing the cases $p>2m$ and $% p=2m.$ Our approach…

Functional Analysis · Mathematics 2015-04-30 Daniel Pellegrino

In this paper, we solve the optimal constant problem in the setting of Ohsawa's generalized $L^{2}$ extension theorem. As applications, we prove a conjecture of Ohsawa and the extended Suita conjecture, we also establish some relations…

Complex Variables · Mathematics 2015-06-23 Qi'an Guan , Xiangyu Zhou

We study the asymptotics for jump-penalized least squares regression aiming at approximating a regression function by piecewise constant functions. Besides conventional consistency and convergence rates of the estimates in $L^2([0,1))$ our…

Statistics Theory · Mathematics 2009-03-02 Leif Boysen , Angela Kempe , Volkmar Liebscher , Axel Munk , Olaf Wittich