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Well known to the machine learning community, the random feature model is a parametric approximation to kernel interpolation or regression methods. It is typically used to approximate functions mapping a finite-dimensional input space to…

Numerical Analysis · Mathematics 2022-06-23 Nicholas H. Nelsen , Andrew M. Stuart

We suggest a new optimization technique for minimizing the sum $\sum_{i=1}^n f_i(x)$ of $n$ non-convex real functions that satisfy a property that we call piecewise log-Lipschitz. This is by forging links between techniques in computational…

Machine Learning · Computer Science 2019-09-10 Ibrahim Jubran , Dan Feldman

We establish a relation between Lipschitz operator ideals and linear operator ideals, which fits in the framework of Galois connection between lattices. We use this relationship to give a criterion which allow us to recognize when a Banach…

Functional Analysis · Mathematics 2018-07-31 Pablo Turco , Román Villafañe

The purpose of this paper is to study an implicit scheme for a representation of nonexpansive mappings on a closed convex subset of a smooth and uniformly convex Banach space with respect to a left regular sequence of means defined on an…

Functional Analysis · Mathematics 2015-06-10 Ebrahim Soori

Motivated by numerical methods for solving parametric partial differential equations, this paper studies the approximation of multivariate analytic functions by algebraic polynomials. We introduce various anisotropic model classes based on…

Numerical Analysis · Mathematics 2020-01-17 Andrea Bonito , Ronald DeVore , Diane Guignard , Peter Jantsch , Guergana Petrova

We study composition operators on spaces of holomorphic Lipschitz functions defined on the open unit ball of a complex Banach space. Our approach is based on the linearization of the symbol through the holomorphic Lipschitz-free spaces,…

Functional Analysis · Mathematics 2026-05-21 Verónica Dimant , Luis C. García-Lirola , Juan Guerrero-Viu , Antonín Procházka

This paper develops a functional-analytic framework for approximating the push-forward induced by an analytic map from finitely many samples. Instead of working directly with the map, we study the push-forward on the space of locally…

Numerical Analysis · Mathematics 2026-04-22 Isao Ishikawa

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

In this paper, we introduce the concept of nearly convex set-valued mappings and investigate fundamental properties of these mappings. Additionally, we establish a geometric approach for generalized differentiation of nearly convex…

Optimization and Control · Mathematics 2023-02-20 Nguyen Mau Nam , Nguyen Nang Thieu , Nguyen Dong Yen

We consider analytic coupled map lattices over $\Z^d$ with exponentially decaying interaction. We introduce Banach spaces for the infinite-dimensional system that include measures with analytic, exponentially bounded finite dimensional…

chao-dyn · Physics 2007-05-23 Torsten Fischer , Hans Henrik Rugh

Let $X$ be a Banach holomorphic function space on the unit disk. A linear polynomial approximation scheme for $X$ is a sequence of bounded linear operators $T_n:X\to X$ with the property that, for each $f\in X$, the functions $T_n(f)$ are…

Functional Analysis · Mathematics 2020-11-09 Javad Mashreghi , Thomas Ransford

We study approximately orthogonality (in the sense of Dragomir) preserving and reversing operators. We show that for some orthogonality notations, an operator defined from a finite-dimensional Banach space to a normed linear space is…

Functional Analysis · Mathematics 2025-12-11 Divya Khurana

In this article, we consider the problem of approximating a finite set of data (usually huge in applications) by invariant subspaces generated through a small set of smooth functions. The invariance is either by translations under a…

Optimization and Control · Mathematics 2023-11-22 Davide Barbieri , Eugenio Hernández , Carlos Cabrelli , Ursula Molter

This paper provides a numerical approach for solving the linear stochastic Volterra integral equation using Walsh function approximation and the corresponding operational matrix of integration. A convergence analysis and error analysis of…

Numerical Analysis · Mathematics 2024-09-02 Prit Pritam Paikaray , Sanghamitra Beuria , Nigam Chandra Parida

In this paper, we develop an accurate pseudospectral method to approximate numerically the Riesz-Feller operator $D_\gamma^\alpha$ on $\mathbb R$, where $\alpha\in(0,2)$, and $|\gamma|\le\min\{\alpha, 2 - \alpha\}$. This operator can be…

Numerical Analysis · Mathematics 2024-01-17 Carlota M. Cuesta , Francisco de la Hoz , Ivan Girona

A lower semi-definite self-adjoint linear operator in a Hilbert space is taken whose discrete spectrum is not empty and comprises at least several eigenvalues $\lambda_{min}=\lambda_1\leqslant\ldots\leqslant\lambda_m<\sigma_{ess}$. The…

Spectral Theory · Mathematics 2019-02-19 Ruslan Sharipov

Iterative slice-matching procedures are efficient schemes for transferring a source measure to a target measure, especially in high dimensions. These schemes have been successfully used in applications such as color transfer and shape…

Numerical Analysis · Mathematics 2023-10-18 Shiying Li , Caroline Moosmueller

With the aim of representing subsets of Banach spaces as an infinite series using Lipschitz functions, we study a variant of metric frames which we call Lipschitz p-approximate Schauder frames (Lipschitz p-ASFs). We characterize Lipschitz…

Functional Analysis · Mathematics 2022-11-22 K. Mahesh Krishna , P. Sam Johnson

Motivated by applications for simulating quantum many body functions, we propose a new universal ansatz for approximating anti-symmetric functions. The main advantage of this ansatz over previous alternatives is that it is bi-Lipschitz with…

Machine Learning · Computer Science 2025-03-07 Nadav Dym , Jianfeng Lu , Matan Mizrachi

Motivated by noncommutative geometry and quantum physics, the concept of `metric operator field' is introduced. Roughly speaking, a metric operator field is a vector field on a set with values in self tensor product of a bundle of…

Operator Algebras · Mathematics 2019-07-31 Maysam Maysami Sadr