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We consider finite element approximations of ill-posed elliptic problems with conditional stability. The notion of {\emph{optimal error estimates}} is defined including both convergence with respect to mesh parameter and perturbations in…

Numerical Analysis · Mathematics 2024-03-25 Erik Burman , Mihai Nechita , Lauri Oksanen

We consider the vertex-centered finite volume method with first-order conforming ansatz functions. The adaptive mesh-refinement is driven by the local contributions of the weighted-residual error estimator. We prove that the adaptive…

Numerical Analysis · Mathematics 2016-11-24 Christoph Erath , Dirk Praetorius

We provide an abstract framework for optimal goal-oriented adaptivity for finite element methods and boundary element methods in the spirit of [Carstensen et al., Comput. Math. Appl. 67 (2014)]. We prove that this framework covers standard…

Numerical Analysis · Mathematics 2016-11-24 Michael Feischl , Dirk Praetorius , Kristoffer G. van der Zee

We discuss goal-oriented adaptivity in the frame of conforming finite element methods and plain convergence of the related a posteriori error estimator for different general marking strategies. We present an abstract analysis for two…

Numerical Analysis · Mathematics 2024-07-30 Valentin Helml , Michael Innerberger , Dirk Praetorius

This chapter provides an overview of state-of-the-art adaptive finite element methods (AFEMs) for the numerical solution of second-order elliptic partial differential equations (PDEs), where the primary focus is on the optimal interplay of…

Numerical Analysis · Mathematics 2024-04-11 Philipp Bringmann , Ani Miraçi , Dirk Praetorius

In this paper we consider the convergence analysis of adaptive finite element method for elliptic optimal control problems with pointwise control constraints. We use variational discretization concept to discretize the control variable and…

Numerical Analysis · Mathematics 2016-08-31 Wei Gong , Ningning Yan

This is a survey on the theory of adaptive finite element methods (AFEMs), which are fundamental in modern computational science and engineering but whose mathematical assessment is a formidable challenge. We present a self-contained and…

Numerical Analysis · Mathematics 2024-11-20 Andrea Bonito , Claudio Canuto , Ricardo H. Nochetto , Andreas Veeser

We present a powerful general framework for designing data-dependent optimization algorithms, building upon and unifying recent techniques in adaptive regularization, optimistic gradient predictions, and problem-dependent randomization. We…

Machine Learning · Statistics 2015-10-14 Mehryar Mohri , Scott Yang

In this paper, we study an adaptive finite element method for multiple eigenvalue problems of a class of second order elliptic equations. By using some eigenspace approximation technology and its crucial property which is also presented in…

Numerical Analysis · Mathematics 2013-09-18 Xiaoying Dai , Lianhua He , Aihui Zhou

For a generalized Hodge Laplace equation, we prove the quasi-optimal convergence rate of an adaptive mixed finite element method. This adaptive method can control the error in the natural mixed variational norm when the space of harmonic…

Numerical Analysis · Mathematics 2021-03-02 Yuwen Li

We analyze optimal complexity of adaptive finite element methods (AFEMs) for general second-order linear elliptic partial differential equations (PDEs) in the Lax-Milgram setting. To this end, we formulate an adaptive algorithm which steers…

Numerical Analysis · Mathematics 2026-04-21 Thomas Führer , Paula Hilbert , Ani Miraçi , Dirk Praetorius

We derive a posteriori error estimators for an optimal control problem governed by a convection-reaction-diffusion equation; control constraints are also considered. We consider a family of low-order stabilized finite element methods to…

Numerical Analysis · Mathematics 2017-04-24 Alejandro Allendes , Enrique Otarola , Richard Rankin

We consider adaptive finite element methods for second-order elliptic PDEs, where the arising discrete systems are not solved exactly. For contractive iterative solvers, we formulate an adaptive algorithm which monitors and steers the…

Numerical Analysis · Mathematics 2021-07-14 Gregor Gantner , Alexander Haberl , Dirk Praetorius , Stefan Schimanko

We present the first rigorous convergence analysis of the smoothed adaptive finite element method (S-AFEM) proposed in [Mulita, Giani, Heltai: SIAM J. Sci. Comput. 43, 2021]. S-AFEM modifies the classical adaptive finite element method…

Numerical Analysis · Mathematics 2026-01-29 Philipp Bringmann , Christoph Lietz , Dirk Praetorius

This paper focuses on the quasi-optimality of an adaptive nonconforming finite element method for a distributed optimal control problem governed by the Stokes equation. The nonconforming lowest order Crouzeix-Raviart element and piecewise…

Numerical Analysis · Mathematics 2026-03-24 Tooba M. Shaikh , Asha K. Dond

We prove convergence with optimal algebraic rates for an adaptive finite element method for nonlinear equations with strongly monotone operator. Unlike prior works, our analysis also includes the iterative and inexact solution of the…

Numerical Analysis · Mathematics 2018-11-27 Gregor Gantner , Alexander Haberl , Dirk Praetorius , Bernhard Stiftner

We develop all of the components needed to construct an adaptive finite element code that can be used to approximate fractional partial differential equations, on non-trivial domains in $d\geq 1$ dimensions. Our main approach consists of…

Numerical Analysis · Mathematics 2018-02-14 Mark Ainsworth , Christian Glusa

In this paper, we discuss adaptive approximations of an elliptic eigenvalue optimization problem in a phase-field setting by a conforming finite element method. An adaptive algorithm is proposed and implemented in several two dimensional…

Numerical Analysis · Mathematics 2025-03-10 Jing Li , Yifeng Xu , Shengfeng Zhu

We design an adaptive finite element method to approximate the solutions of quasi-linear elliptic problems. The algorithm is based on a Ka\v{c}anov iteration and a mesh adaptation step is performed after each linear solve. The method is…

Numerical Analysis · Mathematics 2010-06-18 Eduardo M. Garau , Pedro Morin , Carlos Zuppa

This paper introduces the first theoretical framework for quantifying the efficiency and performance gain opportunity size of adaptive inference algorithms. We provide new approximate and exact bounds for the achievable efficiency and…

Machine Learning · Computer Science 2024-02-08 Soheil Hor , Ying Qian , Mert Pilanci , Amin Arbabian