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We study Green's matrices for divergence form, second order strongly elliptic systems with bounded measurable coefficients in two dimensional domains. We establish existence, uniqueness, and pointwise estimates of the Green's matrices.

Analysis of PDEs · Mathematics 2009-03-02 Hongjie Dong , Seick Kim

In this article we prove for the first time the $C^s$ boundary regularity for solutions to nonlocal elliptic equations with H\"older continuous coefficients in divergence form in $C^{1,\alpha}$ domains. So far, it was only known that…

Analysis of PDEs · Mathematics 2025-09-18 Minhyun Kim , Marvin Weidner

The standard mixed finite element approximations of Hodge Laplace problems associated with the de Rham complex are based on proper discrete subcomplexes. As a consequence, the exterior derivatives, which are local operators, are computed…

Numerical Analysis · Mathematics 2017-09-26 Jeonghun J. Lee , Ragnar Winther

We prove statistical rates of convergence for kernel-based least squares regression from i.i.d. data using a conjugate gradient algorithm, where regularization against overfitting is obtained by early stopping. This method is related to…

Statistics Theory · Mathematics 2016-07-11 Gilles Blanchard , Nicole Krämer

Most existing methodologies of estimating low-rank matrices rely on Burer-Monteiro factorization, but these approaches can suffer from slow convergence, especially when dealing with solutions characterized by a large condition number,…

Optimization and Control · Mathematics 2024-03-06 Teng Zhang , Xing Fan

Flexible boundary condition methods couple an isolated defect to bulk through the bulk lattice Green's function. The inversion of the force-constant matrix for the lattice Green's function requires Fourier techniques to project out the…

Materials Science · Physics 2010-05-28 M. Ghazisaeidi , D. R. Trinkle

In this paper we propose and analyze inexact and stochastic versions of the CGALP algorithm developed in the authors' previous paper, which we denote ICGALP, that allows for errors in the computation of several important quantities. In…

Optimization and Control · Mathematics 2022-10-20 Antonio Silveti-Falls , Cesare Molinari , Jalal Fadili

Low-rank regularization (LRR) has been widely applied in various machine learning tasks, but the associated optimization is challenging. Directly optimizing the rank function under constraints is NP-hard in general. To overcome this…

Machine Learning · Computer Science 2025-05-22 Naiqi Li , Yuqiu Xie , Peiyuan Liu , Tao Dai , Yong Jiang , Shu-Tao Xia

In this article, by applying the well known method for dealing with $p$-Laplace type elliptic boundary value problems, the authors establish a sharp estimate for the decreasing rearrangement of the gradient of solutions to the Dirichlet and…

Analysis of PDEs · Mathematics 2016-03-03 Sibei Yang , Der-Chen Chang , Dachun Yang , Zunwei Fu

We consider the problem of optimizing the sum of a smooth convex function and a non-smooth convex function using proximal-gradient methods, where an error is present in the calculation of the gradient of the smooth term or in the proximity…

Machine Learning · Computer Science 2011-12-02 Mark Schmidt , Nicolas Le Roux , Francis Bach

This paper is devoted to establishing the pointwise upper and lower bounds estimates of the gradient of the solutions to a class of general elliptic systems with H\"{o}lder continuous coefficients in a narrow region where the upper and…

Analysis of PDEs · Mathematics 2022-03-30 Yan Li

In this work, we investigate the convergence of numerical approximations to coercivity constants of variational problems. These constants are essential components of rigorous error bounds for reduced-order modeling; extension of these…

Numerical Analysis · Mathematics 2022-05-25 Peter Sentz , Jehanzeb Hameed Chaudhry , Luke N. Olson

We propose a new practical adaptive refinement strategy for $hp$-finite element approximations of elliptic problems. Following recent theoretical developments in polynomial-degree-robust a posteriori error analysis, we solve two types of…

Numerical Analysis · Mathematics 2018-10-17 Patrik Daniel , Alexandre Ern , Iain Smears , Martin Vohralík

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 construct finite-dimensional approximations of solution spaces of divergence form operators with $L^\infty$-coefficients. Our method does not rely on concepts of ergodicity or scale-separation, but on the property that the solution space…

Numerical Analysis · Mathematics 2011-08-05 Houman Owhadi , Lei Zhang

We approximate functionals depending on the gradient of $u$ and on the behaviour of $u$ near the discontinuity points, by families of non-local functionals where the gradient is replaced by finite differences. We prove pointwise…

Functional Analysis · Mathematics 2007-05-23 Massimo Gobbino , Maria Giovanna Mora

When solving elliptic partial differential equations in a region containing immersed interfaces (possibly evolving in time), it is often desirable to approximate the problem using an independent background discretisation, not aligned with…

Numerical Analysis · Mathematics 2019-10-29 Luca Heltai , Nella Rotundo

A fundamental problem in numerical analysis and approximation theory is approximating smooth functions by polynomials. A much harder version under recent consideration is to enforce bounds constraints on the approximating polynomial. In…

Numerical Analysis · Mathematics 2021-12-28 Larry Allen , Robert C. Kirby

We develop subrepresentation inequalities for infinitely degenerate metrics, and obtain corresponding Poincare and Sobolev inequalities. We then derive conditions on the degenerate metric under which weak solutions to associated infinitely…

Classical Analysis and ODEs · Mathematics 2016-02-23 Lyudmila Korobenko , Cristian Rios , Eric Sawyer , Ruipeng Shen

Factorization-based gradient descent is a scalable and efficient algorithm for solving low-rank matrix completion. Recent progress in structured non-convex optimization has offered global convergence guarantees for gradient descent under…

Optimization and Control · Mathematics 2021-02-09 Trung Vu , Raviv Raich