English
Related papers

Related papers: Robust error estimation for lowest-order approxima…

200 papers

We consider learning in an adversarial environment, where an $\varepsilon$-fraction of samples from a distribution $P$ are arbitrarily modified (global corruptions) and the remaining perturbations have average magnitude bounded by $\rho$…

Machine Learning · Computer Science 2024-06-26 Sloan Nietert , Ziv Goldfeld , Soroosh Shafiee

Based on relative energy estimates, we study the stability of solutions to the Cahn-Hilliard equation with concentration dependent mobility with respect to perturbations. As a by-product of our analysis, we obtain a weak-strong uniqueness…

Numerical Analysis · Mathematics 2021-02-12 Aaron Brunk , Herbert Egger , Oliver Habrich , Maria Lukacova-Medvidova

We present estimators for a well studied statistical estimation problem: the estimation for the linear regression model with soft sparsity constraints ($\ell_q$ constraint with $0<q\leq1$) in the high-dimensional setting. We first present a…

Statistics Theory · Mathematics 2013-11-11 Li Zhang

We devise a posteriori error estimators for quasi-optimal nonconforming finite element methods approximating symmetric elliptic problems of second and fourth order. These estimators are defined for all source terms that are admissible to…

Numerical Analysis · Mathematics 2025-02-05 Christian Kreuzer , Matthias Rott , Andreas Veeser , Pietro Zanotti

We establish local existence and a quasi-optimal error estimate for piecewise cubic minimizers to the bending energy under a discretized inextensibility constraint. In previous research a discretization is used where the inextensibility…

Numerical Analysis · Mathematics 2025-09-03 Sören Bartels , Balázs Kovács , Dominik Schneider

The association between a continuous and an ordinal variable is commonly modeled through the polyserial correlation model. However, this model, which is based on a partially-latent normality assumption, may be misspecified in practice, due…

Methodology · Statistics 2026-02-11 Max Welz

For elliptic interface problems, this paper studies residual-based a posteriori error estimations for various finite element approximations. For the conforming and the Raviart-Thomas mixed elements in two-dimension and for the…

Numerical Analysis · Mathematics 2016-03-04 Zhiqiang Cai , Cuiyu He , Shun Zhang

Recent works showed that pressure-robust modifications of mixed finite element methods for the Stokes equations outperform their standard versions in many cases. This is achieved by divergence-free reconstruction operators and results in…

Numerical Analysis · Mathematics 2017-12-06 P. L. Lederer , C. Merdon , J. Schöberl

We develop a family of mixed finite element methods for a model of nonlinear poroelasticity where, thanks to a rewriting of the constitutive equations, the permeability depends on the total poroelastic stress and on the fluid pressure and…

Numerical Analysis · Mathematics 2025-02-25 Arbaz Khan , Bishnu P. Lamichhane , Ricardo Ruiz-Baier , Segundo Villa-Fuentes

This guide provides a reference for high-probability regret bounds in empirical risk minimization (ERM). The presentation is modular: we begin with intuition and general proof strategies, then state broadly applicable guarantees under…

Machine Learning · Statistics 2026-03-04 Lars van der Laan

Goal oriented error estimation and adaptive procedures are essential for the accurate and efficient evaluation of numerical simulations that involve complex domains. By locally improving the approximation quality we can solve expensive…

The formation and motion of lattice defects such as cracks, dislocations, or grain boundaries, occurs when the lattice configuration loses stability, that is, when an eigenvalue of the Hessian of the lattice energy functional becomes…

Numerical Analysis · Mathematics 2015-05-13 Matthew Dobson , Mitchell Luskin , Christoph Ortner

A refined a priori error analysis of the lowest order (linear) nonconforming Virtual Element Method (VEM) for approximating a model Poisson problem is developed in both 2D and 3D. A set of new geometric assumptions is proposed on shape…

Numerical Analysis · Mathematics 2019-05-17 Shuhao Cao , Long Chen

In the context of global/goal-oriented error estimation applied to computational mechanics, the need to obtain reliable and guaranteed bounds on the discretization error has motivated the use of residual error estimators. These estimators…

Numerical Analysis · Mathematics 2017-04-25 Florent Pled , Ludovic Chamoin , Pierre Ladevèze

In this paper we present and analyze a weighted residual a posteriori error estimate for an optimal control problem. The problem involves a nondifferentiable cost functional, a state equation with an integral fractional Laplacian, and…

Numerical Analysis · Mathematics 2023-09-18 Fangyuan Wang , Qiming Wang , Zhaojie Zhou

Measuring the stability of conclusions derived from Ordinary Least Squares linear regression is critically important, but most metrics either only measure local stability (i.e. against infinitesimal changes in the data), or are only…

Machine Learning · Statistics 2022-06-07 Ankur Moitra , Dhruv Rohatgi

In this paper, we provide a detailed convergence analysis for a first order stabilized linear semi-implicit numerical scheme for the nonlocal Cahn-Hilliard equation, which follows from consistency and stability estimates for the numerical…

Numerical Analysis · Mathematics 2020-03-17 Xiao Li , Zhonghua Qiao , Cheng Wang

We present and analyze two stabilized finite element methods for solving numerically the Poisson--Nernst--Planck equations. The stabilization we consider is carried out by using a shock detector and a discrete graph Laplacian operator for…

Numerical Analysis · Mathematics 2024-12-24 Jesús Bonilla , Juan Vicente Gutiérrez-Santacreu

This paper studies estimation of linear panel regression models with heterogeneous coefficients, when both the regressors and the residual contain a possibly common, latent, factor structure. Our theory is (nearly) efficient, because based…

Econometrics · Economics 2019-03-01 Marco Avarucci , Paolo Zaffaroni

We study the fundamental problem of high-dimensional mean estimation in a robust model where a constant fraction of the samples are adversarially corrupted. Recent work gave the first polynomial time algorithms for this problem with…

Machine Learning · Computer Science 2018-11-26 Yu Cheng , Ilias Diakonikolas , Rong Ge