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When training automated systems, it has been shown to be beneficial to adapt the representation of data by learning a problem-specific metric. This metric is global. We extend this idea and, for the widely used family of k nearest neighbors…

Machine Learning · Computer Science 2021-09-30 Jan Philip Göpfert , Heiko Wersing , Barbara Hammer

We study universal approximation of continuous functionals on compact subsets of products of Hilbert spaces. We prove that any such functional can be uniformly approximated by models that first take finitely many continuous linear…

Machine Learning · Computer Science 2026-02-04 Andrey Krylov , Maksim Penkin

We study supersolutions and superharmonic functions related to problems involving nonlocal operators with Orlicz growth, which are crucial tools for the development of nonlocal nonlinear potential theory. We provide several fine properties…

Analysis of PDEs · Mathematics 2023-11-03 Minhyun Kim , Se-Chan Lee

A multiscale numerical method is proposed for the solution of semi-linear elliptic stochastic partial differential equations with localized uncertainties and non-linearities, the uncertainties being modeled by a set of random parameters. It…

Numerical Analysis · Mathematics 2019-01-23 Anthony Nouy , Florent Pled

We establish a new type of local asymptotic formula for the Green's function ${\mathcal G}_t(x,y)$ of a uniformly parabolic linear operator $\partial_t - L$ with non-constant coefficients using dilations and Taylor expansions at a point…

Analysis of PDEs · Mathematics 2015-05-14 Radu Constantinescu , Nick Costanzino , Anna L Mazzucato , Victor Nistor

The aim of this work is to establish numerous interrelated gradient estimates in the nonlinear nonlocal setting. First of all, we prove that weak solutions to a class of homogeneous nonlinear nonlocal equations of possibly arbitrarily low…

Analysis of PDEs · Mathematics 2024-08-09 Lars Diening , Kyeongbae Kim , Ho-Sik Lee , Simon Nowak

We study the optimal approximation of the solution of an operator equation Au=f by linear and nonlinear mappings. We identify those cases where optimal nonlinear approximation is better than optimal linear approximation.

Numerical Analysis · Mathematics 2025-10-20 Stephan Dahlke , Erich Novak , Winfried Sickel

We study $H^1$ versus $C^1$ local minimizers for functionals defined on spaces of symmetric functions, namely functions that are invariant by the action of some subgroups of $\mathcal{O}(N)$. These functionals, in many cases, are associated…

Analysis of PDEs · Mathematics 2015-05-08 Leonelo Iturriaga , Ederson Moreira dos Santos , Pedro Ubilla

We aim to study nonnegative, global solutions to a general class of nonlocal parabolic equations with bounded measurable coefficients. First, we prove a Widder-type theorem. Such a result has previously been studied only for certain…

Analysis of PDEs · Mathematics 2025-05-14 Naian Liao , Marvin Weidner

We show that weak solutions to the strongly-coupled system of nonlocal equations of linearized peridynamics belong to a potential space with higher integrability. Specifically, we show a function that measures local fractional derivatives…

Analysis of PDEs · Mathematics 2019-06-20 James Scott , Tadele Mengesha

We establish new Harnack estimates that defy the waiting-time phenomenon for global solutions to nonlocal parabolic equations. Our technique allows us to consider general nonlocal operators with bounded measurable coefficients. Moreover, we…

Analysis of PDEs · Mathematics 2025-05-14 Naian Liao , Marvin Weidner

Approximation of entire functions by their pad\'e approximants has been examined in the past. It is true that generically such an approximation holds. However, examining this problem from another viewpoint, we obtain stronger generic…

Complex Variables · Mathematics 2011-05-17 G. Fournodavlos

This paper proposes a novel localized Fourier extension method for approximating non-periodic functions via domain segmentation. By partitioning the computational domain into subregions with uniform discretization scales, the method…

Numerical Analysis · Mathematics 2025-08-29 Zhenyu Zhao , Yanfei Wang

A local projection model is defined by a set of linear regressions that account for the associations between exogenous variables and an endogenous variable observed at different time points. While it is standard practice to separately…

Methodology · Statistics 2020-07-14 Masahiro Tanaka

In this paper, we obtain Cordes-Nirenberg type estimates for nonlocal parabolic equations on the more flexible solution space $L^{\iy}_T(L^1_{\om})$ than the classical solution space $\rB(\BR^n_T)$ consisting of all bounded functions on…

Classical Analysis and ODEs · Mathematics 2015-08-18 Yong-Cheol Kim , Ki-Ahm Lee

Given a model in algebraic statistics and some data, the likelihood function is a rational function on a projective variety. Algebraic algorithms are presented for computing all critical points of this function, with the aim of identifying…

Statistics Theory · Mathematics 2007-06-13 Serkan Hosten , Amit Khetan , Bernd Sturmfels

Using the theory of evolutionary equations, we consider abstract differential equations including non-local integral operators. After providing a condition for the well-posedness of the addressed equation we consider a numerical method of…

Numerical Analysis · Mathematics 2026-01-19 Sebastian Franz , Sascha Trostorff

The approximation in the sense of $\Gamma$-convergence of nonisotropic Griffith-type functionals, with $p-$growth ($p>1$) in the symmetrized gradient, by means of a suitable sequence of non-local convolution type functionals defined on…

Analysis of PDEs · Mathematics 2021-09-02 Fernando Farroni , Giovanni Scilla , Francesco Solombrino

The celebrated Otto calculus has established itself as a powerful tool for proving quantitative energy dissipation estimates and provides with an elegant geometric interpretation of certain functional inequalities such as the Logarithmic…

Classical Analysis and ODEs · Mathematics 2021-10-26 Gauthier Clerc , Giovanni Conforti , Ivan Gentil

We propose to approximate the conditional expectation of a spatial random variable given its nearest-neighbour observations by an additive function. The setting is meaningful in practice and requires no unilateral ordering. It is capable of…

Statistics Theory · Mathematics 2016-03-28 Zudi Lu , Arvid Lundervold , Dag Tjøstheim , Qiwei Yao
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