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Solving systems of linear equations is a problem occuring frequently in water engineering applications. Usually the size of the problem is too large to be solved via direct factorization. One can resort to iterative approaches, in…

Machine Learning · Computer Science 2019-06-18 Johannes Sappl , Laurent Seiler , Matthias Harders , Wolfgang Rauch

The delay Lyapunov equation is an important matrix boundary-value problem which arises as an analogue of the Lyapunov equation in the study of time-delay systems $\dot{x}(t) = A_0x(t)+A_1x(t-\tau)+B_0u(t)$. We propose a new algorithm for…

Numerical Analysis · Mathematics 2018-10-16 Elias Jarlebring , Federico Poloni

Solving symmetric positive definite linear problems is a fundamental computational task in machine learning. The exact solution, famously, is cubicly expensive in the size of the matrix. To alleviate this problem, several linear-time…

Machine Learning · Computer Science 2017-06-02 Filip de Roos , Philipp Hennig

Large linear systems are ubiquitous in modern computational science and engineering. The main recipe for solving them is the use of Krylov subspace iterative methods with well-designed preconditioners. Recently, GNNs have been shown to be a…

Machine Learning · Computer Science 2025-02-04 Vladislav Trifonov , Alexander Rudikov , Oleg Iliev , Yuri M. Laevsky , Ivan Oseledets , Ekaterina Muravleva

Parametric linear systems are linear systems of equations in which some symbolic parameters, that is, symbols that are not considered to be candidates for elimination or solution in the course of analyzing the problem, appear in the…

Rings and Algebras · Mathematics 2025-09-01 Robert M. Corless , Mark Giesbrecht , Leili Rafiee Sevyeri , B. David Saunders

We study first-order methods with preconditioning for solving structured nonlinear convex optimization problems. We propose a new family of preconditioners generated by symmetric polynomials. They provide first-order optimization methods…

Optimization and Control · Mathematics 2023-01-31 Nikita Doikov , Anton Rodomanov

Uni- and bivariate data smoothing with spline functions is a well established method in nonparametric regression analysis. The extension to multivariate data is straightforward, but suffers from exponentially increasing memory and…

Numerical Analysis · Mathematics 2024-12-20 Martin Siebenborn , Julian Wagner

The discontinuous Galerkin time-stepping method has many advantageous properties for solving parabolic equations. However, it requires the solution of a large nonsymmetric system at each time-step. This work develops a fully robust and…

Numerical Analysis · Mathematics 2025-01-29 Iain Smears

The Shifted Boundary Method (SBM) trades some part of the burden of body-fitted meshing for increased algebraic complexity. While the resulting linear systems retain the standard $\mathcal{O}(h^{-2})$ conditioning of second-order operators,…

Numerical Analysis · Mathematics 2026-01-16 Michał Wichrowski , Ajay Ajith

A preconditioning strategy is proposed for the iterative solve of large numbers of linear systems with parameter-dependent matrix and right-hand side which arise during the computation of solution statistics of stochastic elliptic partial…

Numerical Analysis · Mathematics 2025-06-24 Nicolas Venkovic , Paul Mycek , Olivier Le Maître

Although some preconditioners are available for solving dense linear systems, there are still many matrices for which preconditioners are lacking, in particular in cases where the size of the matrix $N$ becomes very large. There remains…

Numerical Analysis · Mathematics 2016-02-05 Pieter Coulier , Hadi Pouransari , Eric Darve

We propose a two-level iterative scheme for solving general sparse linear systems. The proposed scheme consists of a sparse preconditioner that increases the skew-symmetric part and makes the main diagonal of the coefficient matrix as close…

Numerical Analysis · Mathematics 2020-09-16 Murat Manguoglu , Volker Mehrmann

Linear programming (LP) is an extremely useful tool and has been successfully applied to solve various problems in a wide range of areas, including operations research, engineering, economics, or even more abstract mathematical areas such…

Data Structures and Algorithms · Computer Science 2020-03-19 Agniva Chowdhury , Palma London , Haim Avron , Petros Drineas

In this paper, we present and analyze methods for solving a system of linear equations over idempotent semifields. The first method is based on the pseudo-inverse of the system matrix. We then present a specific version of Cramer's rule…

Commutative Algebra · Mathematics 2019-06-25 Fateme Olia , Shaban Ghalandarzadeh , Amirhossein Amiraslani , Sedighe Jamshidvand

Given a full column rank matrix $A \in \mathbb{R}^{m\times n}$ ($m\geq n$), we consider a special class of linear systems of the form $A^\top Ax=A^\top b+c$ with $x, c \in \mathbb{R}^{n}$ and $b \in \mathbb{R}^{m}$. The occurrence of $c$ in…

Numerical Analysis · Mathematics 2019-11-04 Henri Calandra , Serge Gratton , Elisa Riccietti , Xavier Vasseur

A method of numerically solving the Maxwell equations is considered for modeling harmonic electromagnetic fields. The vector finite element method makes it possible to obtain a physically consistent discretization of the differential…

Numerical Analysis · Mathematics 2026-01-05 Andrew V. Terekhov

A preconditioned, multipole-accelerated, Krylov-subspace iterative algorithm for the electromagnetic scattering analysis of three dimensional (3D), arbitrary shaped dielectric structures composed of single and multi-layered dielectric…

Computational Physics · Physics 2017-04-25 Hamid T. Chorsi

When an iterative method is applied to solve the linear equation system in interior point methods (IPMs), the attention is usually placed on accelerating their convergence by designing appropriate preconditioners, but the linear solver is…

Optimization and Control · Mathematics 2023-04-28 Filippo Zanetti , Jacek Gondzio

Discretization of flow in fractured porous media commonly lead to large systems of linear equations that require dedicated solvers. In this work, we develop an efficient linear solver and its practical implementation for mixed-dimensional…

Numerical Analysis · Mathematics 2023-02-08 Xiaozhe Hu , Eirik Keilegavlen , Jan M. Nordbotten

This paper develops the preconditioning technique as a method to address the accuracy issue caused by ill-conditioning. Given a preconditioner $M$ for an ill-conditioned linear system $Ax=b$, we show that, if the inverse of the…

Numerical Analysis · Mathematics 2017-05-15 Qiang Ye