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Motivated by polynomial approximations of differential forms, we study analytical and numerical properties of a polynomial interpolation problem that relies on function averages over interval segments. The usage of segment data gives rise…

Numerical Analysis · Mathematics 2023-09-04 Ludovico Bruni Bruno , Wolfgang Erb

Best simultaneous approximation (BSA) for finitely or infinitely many functions are considered under the uniform norm and other important norms. Characterization theorems for a BSA from a finite-dimensional subspace are obtained by a…

Combinatorics · Mathematics 2024-04-22 Shinji Tanimoto

The concept of proximate order is widely used in the theories of entire, meromorphic, subharmonic and plurisubharmonic functions. We give a general interpretation of this concept as a proximate growth function relative to a model growth…

Complex Variables · Mathematics 2019-12-03 Bulat N. Khabibullin

Normal multi-scale transform [4] is a nonlinear multi-scale transform for representing geometric objects that has been recently investigated [1, 7, 10]. The restrictive role of the exact order of polynomial reproduction $P_e$ of the…

Numerical Analysis · Mathematics 2013-11-19 Stanislav Harizanov

Let $P=(P_1, P_2, \ldots, P_n)$, $P_i \in \field{R}$ for all $i$, be a signal and let $C$ be a constant. In this work our goal is to find a function $F:[n]\rightarrow \field{R}$ which optimizes the following objective function: $$ \min_{F}…

Data Structures and Algorithms · Computer Science 2015-03-13 Gary L. Miller , Richard Peng , Russell Schwartz , Charalampos E. Tsourakakis

We study the approximation of nonlinear operators between function spaces by transformers. Our approach is to lift functions to measures supported on their graphs and leverage a recently introduced measure-theoretic view of transformers. A…

Machine Learning · Computer Science 2026-05-19 Takashi Furuya , David Mis , Ivan Dokmanić , Maarten V. de Hoop , Matti Lassas

The need for recognition/approximation of functions in terms of elementary functions/operations emerges in many areas of experimental mathematics, numerical analysis, computer algebra systems, model building, machine learning, approximation…

Discrete Mathematics · Computer Science 2021-06-09 Andrzej Odrzywolek

This paper introduces an algorithmic approach to the analysis of bifurcation of limit cycles from the centers of nonlinear continuous differential systems via the averaging method. We develop three algorithms to implement the averaging…

Symbolic Computation · Computer Science 2019-05-10 Bo Huang , Chee Yap

Given a multiplicative function f satisfying |f(n)| <= 1 for all n, the authors study the problem of obtaining explicit upper bounds on the mean-value 1/x |sum_{n <= x} f(n)|.

Number Theory · Mathematics 2009-09-25 Andrew Granville , K. Soundararajan

A function of the empirical characteristic function,exists for the stable distribution, which leads to a linear regression and can be used to estimate the parameters. Two approaches are often used, one to find optimal values of t, but these…

Computation · Statistics 2018-11-06 J. Martin van Zyl

We provide general adaptive upper bounds for estimating nonparametric functionals based on second order U-statistics arising from finite dimensional approximation of the infinite dimensional models. We then provide examples of functionals…

Statistics Theory · Mathematics 2021-06-07 Lin Liu , Rajarshi Mukherjee , James Robins , Eric Tchetgen Tchetgen

We present the mathematical context of the predictive accuracy index and then introduce the definition of integral average transform. We establish the relation of our definition with two variables kernels $K({\bf y},{\bf x})$. As an example…

Cryptography and Security · Computer Science 2021-12-07 J. Galvis , Freddy Hernández-Romero , Francisco Gómez

Functional Principal Component Analysis is a reference method for dimension reduction of curve data. Its theoretical properties are now well understood in the simplified case where the sample curves are fully observed without noise.…

Methodology · Statistics 2025-04-28 Ryad Belhakem , Franck Picard , Vincent Rivoirard , Angelina Roche

The bias of an estimator is defined as the difference of its expected value from the parameter to be estimated, where the expectation is with respect to the model. Loosely speaking, small bias reflects the desire that if an experiment is…

Methodology · Statistics 2018-02-16 Ioannis Kosmidis

Approximate Bayesian computation (ABC) is a widely used inference method in Bayesian statistics to bypass the point-wise computation of the likelihood. In this paper we develop theoretical bounds for the distance between the statistics used…

Statistics Theory · Mathematics 2019-01-03 James Ridgway

We provide comparison principles for convex functions through its proximal mappings. Consequently, we prove that the norm of the proximal operator determines a convex the function up to a constant. A new characterization of Lipschitzianity…

Optimization and Control · Mathematics 2020-07-30 Emilio Vilches

This paper addresses the minimization of a finite sum of prox-convex functions under Lipschitz continuity of each component. We propose two variants of the splitting proximal point algorithms proposed in \cite{Bacak,Bertsekas}: one…

Optimization and Control · Mathematics 2026-01-13 Jose de Brito , Felipe Lara , Tran Van Thang

We consider approximation or recovery of functions based on a finite number of function evaluations. This is a well-studied problem in optimal recovery, machine learning, and numerical analysis in general, but many fundamental insights were…

Numerical Analysis · Mathematics 2026-04-07 David Krieg , Mario Ullrich

Convolution with an appropriate surface measure on a paraboloid is known to define a bounded operator T from L^p(R^d) to L^q(R^d) for certain exponents p,q. By a quasiextremal for the associated inequality, we mean a function f for which…

Classical Analysis and ODEs · Mathematics 2011-06-06 Michael Christ

We consider a type of nonnormal approximation of infinitely divisible distributions that incorporates compound Poisson, Gamma, and normal distributions. The approximation relies on achieving higher orders of cumulant matching, to obtain…

Probability · Mathematics 2013-04-24 Zhiyi Chi
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