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As modern machine learning models continue to advance the computational frontier, it has become increasingly important to develop precise estimates for expected performance improvements under different model and data scaling regimes.…

Machine Learning · Computer Science 2023-06-13 Lechao Xiao , Hong Hu , Theodor Misiakiewicz , Yue M. Lu , Jeffrey Pennington

We study problem-dependent rates, i.e., generalization errors that scale near-optimally with the variance, the effective loss, or the gradient norms evaluated at the "best hypothesis." We introduce a principled framework dubbed "uniform…

Machine Learning · Statistics 2020-12-25 Yunbei Xu , Assaf Zeevi

Interpolation and approximation of functionals with conditionally positive definite kernels is considered on sets of centers that are not determining for polynomials. It is shown that polynomial consistency is sufficient in order to define…

Numerical Analysis · Mathematics 2025-08-26 Oleg Davydov

In this paper, we study a generalized finite element method for solving second-order elliptic partial differential equations with rough coefficients. The method uses local approximation spaces computed by solving eigenvalue problems on…

Numerical Analysis · Mathematics 2025-07-17 Christian Alber , Peter Bastian , Moritz Hauck , Robert Scheichl

Given a function f defined on a bidimensional bounded domain and a positive integer N, we study the properties of the triangulation that minimizes the distance between f and its interpolation on the associated finite element space, over all…

Numerical Analysis · Mathematics 2012-06-06 Jean-Marie Mirebeau

A central question in numerical homogenization of partial differential equations with multiscale coefficients is the accurate computation of effective quantities, such as the homogenized coefficients. Computing homogenized coefficients…

Numerical Analysis · Mathematics 2020-07-22 Assyr Abdulle , Doghonay Arjmand , Edoardo Paganoni

We investigate the asymptotic behavior of Halpern-type iterations applied to quasi-nonexpansive operators arising in best approximation problems over the intersection of finitely many closed convex sets in $\mathbb{R}^n$. Assuming a local…

Optimization and Control · Mathematics 2026-05-29 Pablo Barros , Vincent Guigues , Roger Behling , Luiz-Rafael Santos

We survey recent contributions to finite element exterior calculus on manifolds and surfaces within a comprehensive formalism for the error analysis of vector-valued partial differential equations on manifolds. Our primary focus is on…

Numerical Analysis · Mathematics 2024-01-02 Martin W. Licht

Many data analysis applications deal with large matrices and involve approximating the matrix using a small number of ``components.'' Typically, these components are linear combinations of the rows and columns of the matrix, and are thus…

Data Structures and Algorithms · Computer Science 2007-08-29 Petros Drineas , Michael W. Mahoney , S. Muthukrishnan

This article deals with the error estimates for numerical approximations of the entropy solutions of coupled systems of nonlocal hyperbolic conservation laws. The systems can be strongly coupled through the nonlocal coefficient present in…

Numerical Analysis · Mathematics 2023-08-04 Aekta Aggarwal , Helge Holden , Ganesh Vaidya

We show error estimates for a cut finite element approximation of a second order elliptic problem with mixed boundary conditions. The error estimates are of low regularity type where we consider the case when the exact solution $u \in H^s$…

Numerical Analysis · Mathematics 2020-07-07 Erik Burman , Peter Hansbo , Mats G. Larson

Using the concept of Geometric Weakly Admissible Meshes together with an algorithm based on the classical QR factorization of matrices, we compute efficient points for discrete multivariate least squares approximation and Lagrange…

Numerical Analysis · Mathematics 2009-02-03 Len Bos , Jean-Paul Calvi , Norm Levenberg , Alvise Sommariva , Marco Vianello

In this paper, we apply randomized algorithms to approximate the total least squares (TLS) solution of the problem $Ax\approx b$ in the large-scale discrete ill-posed problems. A regularization technique, based on the multiplicative…

Numerical Analysis · Mathematics 2018-08-09 Liping Zhang , Yimin Wei

This work comprises a detailed theoretical and computational study of the boundary value problem for transversely isotropic linear elastic bodies. General conditions for well-posedness are derived in terms of the material parameters. The…

Numerical Analysis · Mathematics 2018-11-01 Faraniaina Rasolofoson , Beverley Grieshaber , B. Daya Reddy

This note is about promoting singularity subtraction as a helpful tool in the discretization of singular integral operators on curved surfaces. Singular and nearly singular kernels are expanded in series whose terms are integrated on…

Numerical Analysis · Mathematics 2013-01-31 Johan Helsing

The purpose of this work is the study of solution techniques for problems involving fractional powers of symmetric coercive elliptic operators in a bounded domain with Dirichlet boundary conditions. These operators can be realized as the…

Numerical Analysis · Mathematics 2013-02-05 Ricardo H. Nochetto , Enrique Otarola , Abner J. Salgado

The goal of this work is to obtain optimal rates for the convergence problem in mean field control. Our analysis covers cases where the solutions to the limiting problem may not be unique nor stable. Equivalently the value function of the…

Optimization and Control · Mathematics 2023-05-16 Samuel Daudin , François Delarue , Joe Jackson

Suppose that there is a ground set which consists of a large number of vectors in a Hilbert space. Consider the problem of selecting a subset of the ground set such that the projection of a vector of interest onto the subspace spanned by…

Information Theory · Computer Science 2015-07-20 Zhenliang Zhang , Yuan Wang , Edwin K. P. Chong , Ali Pezeshki , Louis Scharf

We introduce a numerical method for approximating arbitrary differential operators on vector fields in the weak form given point cloud data sampled randomly from a $d$ dimensional manifold embedded in $\mathbb{R}^n$. This method generalizes…

Numerical Analysis · Mathematics 2026-01-08 John Wilson Peoples , John Harlim

In finite element methods (FEMs), the accuracy of the solution cannot increase indefinitely because the round-off error increases when the number of degrees of freedom (DoFs) is large enough. This means that the accuracy that can be reached…

Numerical Analysis · Mathematics 2019-12-18 Jie Liu , Matthias Möller , Henk M. Schuttelaars