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A posteriori error estimates are derived in the context of two-dimensional structural elastic shape optimization under the compliance objective. It is known that the optimal shape features are microstructures that can be constructed using…

Numerical Analysis · Mathematics 2015-01-30 Benedict Geihe , Martin Rumpf

We consider mixed finite element approximation of a singularly perturbed fourth-order elliptic problem with two different boundary conditions, and present a new measure of the error, whose components are balanced with respect to the…

Numerical Analysis · Mathematics 2016-09-16 Shaohong Du , Runchang Lin , Zhimin Zhang

Multilevel optimization has gained renewed interest in machine learning due to its promise in applications such as hyperparameter tuning and continual learning. However, existing methods struggle with the inherent difficulty of efficiently…

Machine Learning · Computer Science 2024-10-16 Yuntian Gu , Xuzheng Chen

Mixed-dimensional elliptic equations exhibiting a hierarchical structure are commonly used to model problems with high aspect ratio inclusions, such as flow in fractured porous media. We derive general abstract estimates based on the theory…

Numerical Analysis · Mathematics 2022-04-21 Jhabriel Varela , Elyes Ahmed , Eirik Keilegavlen , Jan Martin Nordbotten , Florin Adrian Radu

In this paper we introduce and analyze the residual-based a posteriori error estimation of the partially penalized immersed finite element method for solving elliptic interface problems. The immersed finite element method can be naturally…

Numerical Analysis · Mathematics 2019-10-18 Cuiyu He , Xu Zhang

A posteriori error estimator is derived for an elliptic interface problem in the fictitious domain formulation with distributed Lagrange multiplier considering a discontinuous Lagrange multiplier finite element space. A posteriori error…

Numerical Analysis · Mathematics 2024-07-02 Najwa Alshehri , Daniele Boffi , Lucia Gastaldi

Stochastic gradient methods are scalable for solving large-scale optimization problems that involve empirical expectations of loss functions. Existing results mainly apply to optimization problems where the objectives are one- or two-level…

Optimization and Control · Mathematics 2018-01-15 Shuoguang Yang , Mengdi Wang , Ethan X. Fang

This paper introduces a new computational methodology for determining a-posteriori multi-objective error estimates for finite-element approximations, and for constructing corresponding (quasi-)optimal adaptive refinements of finite-element…

Numerical Analysis · Mathematics 2016-11-23 E. H. van Brummelen , S. Zhuk , G. J. van Zwieten

We combine a systematic approach for deriving general a posteriori error estimates for convex minimization problems based on convex duality relations with a recently derived generalized Marini formula. The a posteriori error estimates are…

Numerical Analysis · Mathematics 2022-04-25 Sören Bartels , Alex Kaltenbach

This article describes the extension of recent methods for a posteriori error estimation such as dual-weighted residual methods to node-centered finite volume discretizations of second order elliptic boundary value problems including upwind…

Numerical Analysis · Mathematics 2026-02-04 Lutz Angermann

Accurate error estimation is crucial in model order reduction, both to obtain small reduced-order models and to certify their accuracy when deployed in downstream applications such as digital twins. In existing a posteriori error estimation…

Numerical Analysis · Mathematics 2023-07-24 Sridhar Chellappa , Lihong Feng , Peter Benner

Multilevel techniques are efficient approaches for solving the large linear systems that arise from discretized partial differential equations and other problems. While geometric multigrid requires detailed knowledge about the underlying…

Numerical Analysis · Mathematics 2023-01-23 Tareq. U. Zaman , Scott P. MacLachlan , Luke N. Olson , Matt West

This article is a review on basic concepts and tools devoted to a posteriori error estimation for problems solved with the Finite Element Method. For the sake of simplicity and clarity, we mostly focus on linear elliptic diffusion problems,…

Numerical Analysis · Mathematics 2021-10-06 Ludovic Chamoin , Frederic Legoll

We propose a randomized a posteriori error estimator for reduced order approximations of parametrized (partial) differential equations. The error estimator has several important properties: the effectivity is close to unity with prescribed…

Numerical Analysis · Mathematics 2019-04-02 Kathrin Smetana , Olivier Zahm , Anthony T Patera

A residual based {\em a posteriori} error estimator is derived for a quadratic finite element method (fem) for the elliptic obstacle problem. The error estimator involves various residuals consisting the data of the problem, discrete…

Numerical Analysis · Mathematics 2014-04-14 Thirupathi Gudi , Kamana Porwal

We study a general class of bilevel problems, consisting in the minimization of an upper-level objective which depends on the solution to a parametric fixed-point equation. Important instances arising in machine learning include…

Machine Learning · Statistics 2020-07-13 Riccardo Grazzi , Luca Franceschi , Massimiliano Pontil , Saverio Salzo

This work derives a residual-based a posteriori error estimator for reduced models learned with non-intrusive model reduction from data of high-dimensional systems governed by linear parabolic partial differential equations with control…

Numerical Analysis · Mathematics 2020-05-13 Wayne Isaac Tan Uy , Benjamin Peherstorfer

In this paper, we study a modified residual-based a posteriori error estimator for the nonconforming linear finite element approximation to the interface problem. The reliability of the estimator is analyzed by a new and direct approach…

Numerical Analysis · Mathematics 2016-11-23 Zhiqiang Cai , Cuiyu He , Shun Zhang

A residual-based a posteriori error estimator is proposed for the incompressible Oseen problem in the convection-dominated regime. The SUPG/PSPG/grad-div stabilized finite element method is used as discretization. The error estimator…

Numerical Analysis · Mathematics 2026-04-28 Muhammad Afzal , Naveed Ahmed , Volker John

The Reduced Basis (RB) method is a well established method for the model order reduction of problems formulated as parametrized partial differential equations. One crucial requirement for the application of RB schemes is the availability of…

Numerical Analysis · Mathematics 2016-11-25 Andreas Buhr , Christian Engwer , Mario Ohlberger , Stephan Rave