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We prove quasi-optimal a priori error estimates for finite element approximations of boundary normal fluxes in the $L^2$-norm. Our results are valid for a variety of different schemes for weakly enforcing Dirichlet boundary conditions…

Numerical Analysis · Mathematics 2014-01-28 Mats G. Larson , Andre Massing

We consider a diffusion equation with highly oscillatory coefficients that admits a homogenized limit. As an alternative to standard corrector problems, we introduce here an embedded corrector problem, written as a diffusion equation in the…

Numerical Analysis · Mathematics 2014-12-22 Eric Cances , Virginie Ehrlacher , Frederic Legoll , Benjamin Stamm

We present norm estimates for solutions of first and second order elliptic BVPs of the Dirac operator considered over a bounded and smooth domain of the n-dimension Euclidean space. The solutions whose norms to be estimated are in some…

Functional Analysis · Mathematics 2014-01-20 Dejenie A. Lakew

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

We propose a new approach to non-parametric density estimation that is based on regularizing a Sobolev norm of the density. This method is statistically consistent, and makes the inductive bias of the model clear and interpretable. While…

Machine Learning · Statistics 2024-02-15 Mark Kozdoba , Binyamin Perets , Shie Mannor

Many randomized approximation algorithms operate by giving a procedure for simulating a random variable $X$ which has mean $\mu$ equal to the target answer, and a relative standard deviation bounded above by a known constant $c$. Examples…

Computation · Statistics 2019-08-16 Mark Huber

Primal-dual splitting involving proximity operators in order to be able to find some approximation to the minimizer for a general form of Tikhonov type functional is in the focus of this work. This approximation is produced by a pair of…

Numerical Analysis · Mathematics 2019-03-19 Erdem Altuntac

We show, that under natural assumptions, solutions of Dirichlet problems for uniformly elliptic divergence form operator can be approximated pointwise by solutions of some versions of Robin problems. The proof is based on stochastic…

Analysis of PDEs · Mathematics 2023-10-05 Andrzej Rozkosz , Leszek Slominski

In this paper we propose and analyze two dual methods based on inexact gradient information and averaging that generate approximate primal solutions for smooth convex optimization problems. The complicating constraints are moved into the…

Optimization and Control · Mathematics 2013-02-14 Ion Necoara , Valentin Nedelcu

This paper studies formulations of second-order elliptic partial differential equations in nondivergence form on convex domains as equivalent variational problems. The first formulation is that of Smears \& S\"uli [SIAM J.\ Numer.\ Anal.\…

Numerical Analysis · Mathematics 2017-01-17 Dietmar Gallistl

Convergence results are shown for full discretizations of quasilinear parabolic partial differential equations on evolving surfaces. As a semidiscretization in space the evolving surface finite element method is considered, using a…

Numerical Analysis · Mathematics 2015-04-01 Balázs Kovács , Christian Andreas Power Guerra

In this paper, we establish sublinear and linear convergence of fixed point iterations generated by averaged operators in a Hilbert space. Our results are achieved under a bounded H\"older regularity assumption which generalizes the…

Optimization and Control · Mathematics 2018-08-16 Jonathan M. Borwein , Guoyin Li , Matthew K. Tam

We analyze the error of the WEB-S finite element method applied to elliptic systems with non-cooperative dominant coupling,with a mixed Dirichlet/Neumann/Robin boundary condition. This problem is strongly related to a posteriori error…

Numerical Analysis · Mathematics 2018-06-28 Ayan Chakraborty , B. V. Rathish Kumar

This paper presents a regularization technique incorporating a non-convex and non-smooth term, $\ell_{1}^{2}-\eta\ell_{2}^{2}$, with parameters $0<\eta\leq 1$ designed to address ill-posed linear problems that yield sparse solutions. We…

Optimization and Control · Mathematics 2025-06-16 Long Li , Liang Ding

A space-discretization for the elastic flow of inextensible curves is devised and quasi-optimal convergence of the corresponding semi-discrete problem is proved for a suitable discretization of the nonlinear inextensibility constraint.…

Numerical Analysis · Mathematics 2025-04-07 Sören Bartels , Klaus Deckelnick , Dominik Schneider

A space-time interface-fitted approximation of an inverse source problem for the advection-diffusion equation with moving subdomains is investigated. The problem is reformulated as an optimization problem using Tikhonov regularization. A…

Numerical Analysis · Mathematics 2025-02-11 Thi Thanh Mai Ta , Quang Huy Nguyen , Dinh Nho Hào

We propose and analyze an unfitted finite element method for solving elliptic problems on domains with curved boundaries and interfaces. The approximation space on the whole domain is obtained by the direct extension of the finite element…

Numerical Analysis · Mathematics 2021-12-28 Fanyi Yang , Xiaoping Xie

We analyse a diffuse interface type approximation, known as the diffuse domain approach, of a linear coupled bulk-surface elliptic partial differential system. The well-posedness of the diffuse domain approximation is shown using weighted…

Analysis of PDEs · Mathematics 2015-02-18 Helmut Abels , Kei Fong Lam , Björn Stinner

In this work, we present a novel error analysis for recovering a spatially dependent diffusion coefficient in an elliptic or parabolic problem. It is based on the standard regularized output least-squares formulation with an $H^1(\Omega)$…

Numerical Analysis · Mathematics 2020-10-07 Bangti Jin , Zhi Zhou

We provide the first proof of convergence for normalized error feedback algorithms across a wide range of machine learning problems. Despite their popularity and efficiency in training deep neural networks, traditional analyses of error…

Machine Learning · Computer Science 2024-10-23 Sarit Khirirat , Abdurakhmon Sadiev , Artem Riabinin , Eduard Gorbunov , Peter Richtárik
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