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Related papers: Necessity of numerical smoothness

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In the last several years, the intimate connection between convex optimization and learning problems, in both statistical and sequential frameworks, has shifted the focus of algorithmic machine learning to examine this interplay. In…

Machine Learning · Computer Science 2014-07-23 Mehrdad Mahdavi

We investigate the problem of showing that the values of a given polynomial are smooth (i.e., have no large prime factors) a positive proportion of the time. Although some results exist that bound the number of smooth values of a polynomial…

Number Theory · Mathematics 2007-05-23 Greg Martin

The data functions that are studied in the course of functional data analysis are assembled from discrete data, and the level of smoothing that is used is generally that which is appropriate for accurate approximation of the conceptually…

Statistics Theory · Mathematics 2013-12-19 Raymond J. Carroll , Aurore Delaigle , Peter Hall

We consider the problem of estimating an unknown function f* and its partial derivatives from a noisy data set of n observations, where we make no assumptions about f* except that it is smooth in the sense that it has square integrable…

Machine Learning · Statistics 2024-05-17 Eunji Lim

We present effective numerical algorithms for locally recovering unknown governing differential equations from measurement data. We employ a set of standard basis functions, e.g., polynomials, to approximate the governing equation with high…

Numerical Analysis · Mathematics 2020-05-05 Kailiang Wu , Dongbin Xiu

We consider a linear partial integro-differential equation that arises in the modeling of various physical and biological processes. We study the problem in a spatial periodic domain. We analyze numerical stability and numerical convergence…

Numerical Analysis · Mathematics 2010-05-31 Samir Kumar Bhowmik

Most approximation methods in high dimensions exploit smoothness of the function being approximated. These methods provide poor convergence results for non-smooth functions with kinks. For example, such kinks can arise in the uncertainty…

Numerical Analysis · Mathematics 2019-02-19 Barbara Fuchs , Jochen Garcke

Towards identifying the number of minimal surfaces sharing the same boundary from the geometry of the boundary, we propose a numerical scheme with high speed and high accuracy. Our numerical scheme is based on the method of fundamental…

Numerical Analysis · Mathematics 2022-12-14 Koya Sakakibara , Yuuki Shimizu

The problem of testing hypothesis that a density function has no more than $\mu$ derivatives versus it has more than $\mu$ derivatives is considered. For a solution, the $L^2$ norms of wavelet orthogonal projections on some orthogonal…

Statistics Theory · Mathematics 2018-09-11 Bogdan Ćmiel , Karol Dziedziul , Barbara Wolnik

We prove convergence of the spectral element method for piecewise polynomial collocation applied to periodic boundary value problems for functional differential equations. In particular, we prove that the numerical collocation solution…

Numerical Analysis · Mathematics 2025-10-27 Alessia andò , Jan Sieber

We have presented some practical consequences on the molecular-dynamics simulations arising from the numerical algorithm published recently in paper Int. J. Mod. Phys. C 16, 413 (2005). The algorithm is not a finite-difference method and…

Exactly Solvable and Integrable Systems · Physics 2015-06-26 B. Brzostowski , M. R. Dudek , B. Grabiec , T. Nadzieja

When implementing regular enough functions (e.g., elementary or special functions) on a computing system, we frequently use polynomial approximations. In most cases, the polynomial that best approximates (for a given distance and in a given…

Mathematical Software · Computer Science 2007-05-23 Nicolas Brisebarre , Jean-Michel Muller

In this paper, we issue an error analysis for integration over discrete surfaces using the surface parametrization presented in [PS22] as well as prove why even-degree polynomials exhibit a higher convergence rate than odd-degree…

Numerical Analysis · Mathematics 2024-02-06 Gentian Zavalani , Elima Shehu , Michael Hecht

A soft-max function has two main efficiency measures: (1) approximation - which corresponds to how well it approximates the maximum function, (2) smoothness - which shows how sensitive it is to changes of its input. Our goal is to identify…

Machine Learning · Computer Science 2026-01-01 Alessandro Epasto , Mohammad Mahdian , Vahab Mirrokni , Manolis Zampetakis

Periodic solutions of delay equations are usually approximated as continuous piecewise polynomials on meshes adapted to the solutions' profile. In practical computations this affects the regularity of the (coefficients of the) linearized…

Numerical Analysis · Mathematics 2025-04-18 Dimitri Breda , Davide Liessi , Rossana Vermiglio

Symmetries play an critical role in finding analytic solutions to nonlinear differential equations. A symmetry is a mapping of the solutions of the differential equation into the solutions and have been studied extensively for over a…

Mathematical Physics · Physics 2014-10-01 Stanly Steinberg , Rubens de Melo Marinho Junior

Isotonic regression provides a flexible, tuning-free approach to estimating monotonic functions without imposing global curvature constraints, yet the estimated regression function is inherently a step function. This paper addresses a key…

Methodology · Statistics 2026-05-19 Timo Kuosmanen , Juan F. Monge , José L. Ruiz , Xun Zhou

The main purpose of this paper is to prove some density results of polynomials in Fock spaces of slice regular functions. The spaces can be of two different kinds since they are equipped with different inner products and contain different…

Complex Variables · Mathematics 2018-12-10 Kamal Diki , Sorin G. Gal , Irene Sabadini

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

There are many significant applied contexts that require the solution of discontinuous optimization problems in finite dimensions. Yet these problems are very difficult, both computationally and analytically. With the functions being…

Optimization and Control · Mathematics 2023-05-25 Ying Cui , Junyi Liu , Jong-Shi Pang