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Recently, Adiceam, Beresnevich, Levesley, Velani and Zorin proved a quantitative version of the convergence case of the Khintchine-Groshev theorem for nondegenerate manifolds, motivated by applications to interference alignment. In the…

Number Theory · Mathematics 2016-10-10 Arijit Ganguly , Anish Ghosh

On any metric space, I provide an intrinsic characterization of those complex-valued functions which are uniform limits of Lipschitz functions. There are applications to function theory on complete Riemannian manifolds and, in particular,…

Functional Analysis · Mathematics 2021-05-18 L. A. Coburn

We consider high order approximations of the solution of the stochastic filtering problem, derive their pathwise representation in the spirit of the earlier work of Clark and Davis and prove their robustness property. In particular, we show…

Numerical Analysis · Mathematics 2021-01-12 Dan Crisan , Alexander Lobbe , Salvador Ortiz-Latorre

This paper presents a general study of one-dimensional differentiability for functionals defined on convex domains that are not necessarily open. The local approximation is carried out using affine functionals, as opposed to linear…

Functional Analysis · Mathematics 2025-07-04 Simone Cerreia-Vioglio , Fabio Maccheroni , Massimo Marinacci , Luigi Montrucchio , Lorenzo Stanca

We study two types of approximations of Lipschitz maps with derivatives of maximal slopes on Banach spaces. First, we characterize the Radon-Nikod\'ym property in terms of strongly norm attaining Lipschitz maps and maximal derivative…

Functional Analysis · Mathematics 2024-10-23 Geunsu Choi

We present here a new method for approximating functions defined on superreflexive Banach spaces by differentiable functions with $\alpha$-H\"older derivatives (for some $0<\alpha\leq 1$). The smooth approximation is given by means of an…

Functional Analysis · Mathematics 2016-09-07 Manuel Cepedello Boiso

In this paper we propose a new deterministic approximation method, called discretization approximation, for Bayesian computation. Discretization approximation is very simple to understand and to implement, It only requires calculating…

Computation · Statistics 2026-01-13 Shifeng Xiong

We investigate affine Berkovich spaces over maximally complete fields and prove that they may be approximated by simpler spaces when the only functions we need to evaluate are polynomials of bounded degree. We derive applications to…

Algebraic Geometry · Mathematics 2012-04-17 Jérôme Poineau

In generalized Lebesgue spaces L^{p(.)} with variable exponent p(.) defined on the real axis, we obtain several inequalities of approximation by integral functions of finite degree. Approximation properties of Bernstein singular integrals…

Classical Analysis and ODEs · Mathematics 2021-09-06 Ramazan Akgün

We prove various theorems on approximation using polynomials with integer coefficients in the Bernstein basis of any given order. In the extreme, we draw the coefficients from $\{ \pm 1\}$ only. A basic case of our results states that for…

Information Theory · Computer Science 2022-12-08 C. Sinan Güntürk , Weilin Li

We introduce the generalized notion of semicontinuity of a function defined on a topological space and derive the useful classification of the so-called Lipschitz derivatives of functions defined on a metric space. Secondly, we investigate…

Functional Analysis · Mathematics 2025-09-26 Oleksandr V. Maslyuchenko , Ziemowit M. Wójcicki

We generalize the sparsification algorithm of Batson, Spielman and Srivastava, making one part of the result dimension-independent. In particular, we recover discretization inequalities in $L_2$- and sup-norms on general finite-dimensional…

Numerical Analysis · Mathematics 2026-02-24 Abdellah Chkifa , Matthieu Dolbeault , David Krieg , Mario Ullrich

It is shown here that if $(Y,\|\cdot\|_Y)$ is a Banach space in which martingale differences are unconditional (a UMD Banach space) then there exists $c=c(Y)\in (0,\infty)$ with the following property. For every $n\in \mathbb{N}$ and…

Functional Analysis · Mathematics 2017-01-18 Tuomas Hytönen , Sean Li , Assaf Naor

While efficient distribution learning is no doubt behind the groundbreaking success of diffusion modeling, its theoretical guarantees are quite limited. In this paper, we provide the first rigorous analysis on approximation and…

Machine Learning · Statistics 2023-03-06 Kazusato Oko , Shunta Akiyama , Taiji Suzuki

We show that affine coordinate subspaces of dimension at least two in Euclidean space are of Khintchine type for divergence. For affine coordinate subspaces of dimension one, we prove a result which depends on the dual Diophantine type of…

Number Theory · Mathematics 2017-11-23 Fabian Süess

Many elliptic boundary value problems exhibit an interior regularity property, which can be exploited to construct local approximation spaces that converge exponentially within function spaces satisfying this property. These spaces can be…

Numerical Analysis · Mathematics 2025-07-04 S. Aziz , M. Bauer , M. Bebendorf , T. Rau

Given labeled points in a high-dimensional vector space, we seek a low-dimensional subspace such that projecting onto this subspace maintains some prescribed distance between points of differing labels. Intended applications include…

Machine Learning · Statistics 2018-12-10 Culver McWhirter , Dustin G. Mixon , Soledad Villar

We generalize Bourgain's discretized projection theorem to higher rank situations. Like Bourgain's theorem, our result yields an estimate for the Hausdorff dimension of the exceptional sets in projection theorems formulated in terms of…

Classical Analysis and ODEs · Mathematics 2018-05-10 Weikun He

Laplace's method approximates a target density with a Gaussian distribution at its mode. It is computationally efficient and asymptotically exact for Bayesian inference due to the Bernstein-von Mises theorem, but for complex targets and…

Machine Learning · Computer Science 2026-03-12 Hanlin Yu , Marcelo Hartmann , Bernardo Williams , Mark Girolami , Arto Klami

We consider approximation by functions with finite support and characterize its approximation spaces in terms of interpolation spaces and Lorentz spaces.

Classical Analysis and ODEs · Mathematics 2017-07-05 Bo Ling , Yongping Liu
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