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Low-rank approximation of a matrix by means of structured random sampling has been consistently efficient in its extensive empirical studies around the globe, but adequate formal support for this empirical phenomenon has been missing so…

Numerical Analysis · Mathematics 2016-07-21 Victor Pan , John Svadlenka , Liang Zhao

We consider a saddle point formulation for a sixth order partial differential equation and its finite element approximation, for two sets of boundary conditions. We follow the Ciarlet-Raviart formulation for the biharmonic problem to…

Numerical Analysis · Mathematics 2017-11-17 Jérôme Droniou , Muhammad Ilyas , Bishnu Lamichhane , Glen E. Wheeler

We give an algorithm for computing approximate PSD factorizations of nonnegative matrices. The running time of the algorithm is polynomial in the dimensions of the input matrix, but exponential in the PSD rank and the approximation error.…

Data Structures and Algorithms · Computer Science 2016-02-25 Amitabh Basu , Michael Dinitz , Xin Li

In this work, we investigate the numerical reconstruction of inclusions in a semilinear elliptic equation arising in the mathematical modeling of cardiac ischemia. We propose an adaptive finite element method for the resulting constrained…

Numerical Analysis · Mathematics 2025-08-07 Bangti Jin , Fengru Wang , Yifeng Xu

The regularity of the solution of elliptic partial differential equa- tions in a polygonal domain with re-entrant corners is, in general, reduced compared to the one on a smooth convex domain. This results in a best approximation property…

Numerical Analysis · Mathematics 2017-04-20 Thomas Horger , Petra Pustejovska , Barbara Wohlmuth

This article studies some numerical approximations of the homogenized matrix for stochastic linear elliptic partial differential equations in divergence form. We focus on the case when the underlying random field is a small perturbation of…

Numerical Analysis · Mathematics 2011-02-21 Ronan Costaouec

We prove that the Minimum Distance Problem (MDP) on linear codes over any fixed finite field and parameterized by the input distance bound is W[1]-hard to approximate within any constant factor. We also prove analogous results for the…

Computational Complexity · Computer Science 2024-02-28 Huck Bennett , Mahdi Cheraghchi , Venkatesan Guruswami , João Ribeiro

A matrix optimization problem over an uncertain linear system on finite horizon (abbreviated as MOPUL) is studied, in which the uncertain transition matrix is regarded as a decision variable. This problem is in general NP-hard. By using the…

Optimization and Control · Mathematics 2023-10-31 Jintao Xu , Shu-Cherng Fang , Wenxun Xing

The paper is concerned with the adaptive finite element solution of linear elliptic differential equations using equidistributing meshes. A strategy is developed for defining this type of mesh based on residual-based a posteriori error…

Numerical Analysis · Mathematics 2020-04-20 Yinnian He , Weizhang Huang

In this paper, a direct finite element method is proposed for solving interface problems on unfitted meshes. This new method treats the two interface conditions as an $H^{\frac12}(\Gamma)\times H^{-\frac12}(\Gamma)$ pair for the mutual…

Numerical Analysis · Mathematics 2025-08-19 Jun Hu , Limin Ma

We describe several algorithms for matrix completion and matrix approximation when only some of its entries are known. The approximation constraint can be any whose approximated solution is known for the full matrix. For low rank…

Numerical Analysis · Mathematics 2014-07-01 Gil Shabat , Yaniv Shmueli , Amir Averbuch

In this paper, we consider the matrices approximated in H2 format. The direct solution, as well as the preconditioning, of systems with such matrices is a challenging problem. We propose a non-extensive sparse factorization of the H2 matrix…

Numerical Analysis · Mathematics 2018-05-01 Daria Sushnikova , Ivan Oseledets

We propose a numerical method to approximate the solution of second order elliptic problems in nonvariational form. The method is of Galerkin type using conforming finite elements and applied directly to the nonvariational (nondivergence)…

Numerical Analysis · Mathematics 2011-05-19 Omar Lakkis , Tristan Pryer

We investigate the potential of applying (D)NN ((deep) neural networks) for approximating nonlinear mappings arising in the finite element discretization of nonlinear PDEs (partial differential equations). As an application, we apply the…

Numerical Analysis · Mathematics 2019-11-14 Tuyen Tran , Aidan Hamilton , Maricela Best McKay , Benjamin Quiring , Panayot S. Vassilevski

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

By considering an empirical approximation, and a new class of operators that we will call walking operators, we construct, for any positive ND-toeplitz matrix, an infinite in all dimensions matrix, for which the inverse approximates the…

Spectral Theory · Mathematics 2007-05-23 Rami Kanhouche

In this paper, we study a class of approximation problems, appearing in data approximation and signal processing. The approximations are constructed as combinations of polynomial splines (piecewise polynomials), whose parameters are subject…

Optimization and Control · Mathematics 2015-03-05 Zahra Roshan Zamir , Nadezda Sukhorukova

Explicit time advancement for continuous finite elements requires the inversion of a global mass matrix. For spectral element simulations on quadrilaterals and hexahedra, there is an accurate approximate mass matrix which is diagonal,…

Analysis of PDEs · Mathematics 2019-06-27 Jay Appleton , Brian Helenbrook

We present a reduced basis (RB) method for parametrized linear elliptic partial differential equations (PDEs) in a least-squares finite element framework. A rigorous and reliable error estimate is developed, and is shown to bound the error…

Numerical Analysis · Mathematics 2020-09-24 Jehanzeb Hameed Chaudhry , Luke N. Olson , Peter Sentz

A multilevel adaptive refinement strategy for solving linear elliptic partial differential equations with random data is recalled in this work. The strategy extends the a posteriori error estimation framework introduced by Guignard and…

Numerical Analysis · Mathematics 2022-02-21 Alex Bespalov , David J. Silvester
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