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A combination of block-Jacobi and deflation preconditioning is used to solve a high-order discontinuous element-based collocation discretization of the Schur complement of the Poisson-Neumann system as arises in the operator splitting of…

Numerical Analysis · Mathematics 2016-01-15 Sumedh Joshi , Peter Diamessis

In this paper, we revisit the large-scale constrained linear regression problem and propose faster methods based on some recent developments in sketching and optimization. Our algorithms combine (accelerated) mini-batch SGD with a new…

Machine Learning · Computer Science 2018-02-12 Di Wang , Jinhui Xu

An inherent regularization strategy and block Schur complement preconditioning are studied for linear poroelasticity problems discretized using the lowest-order weak Galerkin FEM in space and the implicit Euler scheme in time. At each time…

Numerical Analysis · Mathematics 2025-07-31 Weizhang Huang , Zhuoran Wang

In this work, the matrix-free solution of quasi-static phase-field fracture problems is further investigated. More specifically, we consider a quasi-monolithic formulation in which the irreversibility constraint is imposed with a…

Numerical Analysis · Mathematics 2024-08-27 Leon Maximilian Kolditz , Thomas Wick

A two-step preconditioned iterative method based on the Hermitian/Skew-Hermitian splitting is applied to the solution of nonsymmetric linear systems arising from the Finite Element approximation of convection-diffusion equations. The…

Numerical Analysis · Mathematics 2008-07-23 Alessandro Russo , Cristina Tablino Possio

This paper introduces a novel optimization algorithm designed for nonlinear least-squares problems. The method is derived by preconditioning the gradient descent direction using the Singular Value Decomposition (SVD) of the Jacobian. This…

Numerical Analysis · Mathematics 2026-02-11 Zhipeng Chang , Wenrui Hao , Nian Liu

We consider the minimum-cut partitioning of a graph into more than two parts using spectral methods. While there exist well-established spectral algorithms for this problem that give good results, they have traditionally not been well…

Data Structures and Algorithms · Computer Science 2014-08-04 Maria A. Riolo , M. E. J. Newman

Iterative solvers preconditioned with algebraic multigrid have been devised as an optimal technology to speed up the response of large sparse linear systems. In this work, this technique was implemented in the framework of the dual…

Geophysics · Physics 2020-01-22 M. A. Sbai , A. Larabi

In this paper, we propose a stochastic method for solving equality constrained optimization problems that utilizes predictive variance reduction. Specifically, we develop a method based on the sequential quadratic programming paradigm that…

Optimization and Control · Mathematics 2023-03-28 Albert S. Berahas , Jiahao Shi , Zihong Yi , Baoyu Zhou

We propose a novel preconditioned inexact primal-dual interior point method for constrained convex quadratic programming problems. The algorithm we describe invokes the preconditioned conjugate gradient method on a new reduced Schur…

Numerical Analysis · Mathematics 2021-12-28 Samah Karim , Edgar Solomonik

When given a generalized matrix separation problem, which aims to recover a low rank matrix $L_0$ and a sparse matrix $S_0$ from $M_0=L_0+HS_0$, the work \cite{CW25} proposes a novel convex optimization problem whose objective function is…

Optimization and Control · Mathematics 2026-05-05 Xuemei Chen , Owen Deen

Linear systems with large differences between coefficients ("discontinuous coefficients") arise in many cases in which partial differential equations(PDEs) model physical phenomena involving heterogeneous media. The standard approach to…

Mathematical Software · Computer Science 2009-05-04 Dan Gordon , Rachel Gordon

In this paper, we propose a parameter-robust preconditioner for the coupled Stokes-Darcy problem equipped with various boundary conditions, enforcing the mass conservation at the interface via a Lagrange multiplier. We rigorously establish…

Numerical Analysis · Mathematics 2025-12-01 Xiaozhe Hu , Miroslav Kuchta , Kent-Andre Mardal , Xue Wang

We introduce an iterative method named GPMR for solving 2x2 block unsymmetric linear systems. GPMR is based on a new process that reduces simultaneously two rectangular matrices to upper Hessenberg form and that is closely related to the…

Numerical Analysis · Mathematics 2021-11-16 Alexis Montoison , Dominique Orban

In this study, we propose the lopsided HSS (LHSS) iteration method for solving a class of complex symmetric indefinite systems of linear equations. This method employs an alternating iterative scheme, where each iteration entails solving…

Numerical Analysis · Mathematics 2025-11-27 Yusong Zhang , Zeng-Qi Wang

Linear minimum mean square error (LMMSE) estimation is often ill-conditioned, suggesting that unconstrained minimization of the mean square error is an inadequate approach to filter design. To address this, we first develop a unifying…

Signal Processing · Electrical Eng. & Systems 2022-03-23 Edwin K. P. Chong

In this paper we introduce an algebraic recursive multilevel incomplete factorization preconditioner, based on a distributed Schur complement formulation, for solving general linear systems. The novelty of the proposed method is to combine…

Numerical Analysis · Mathematics 2015-09-23 Yiming Bu , Bruno Carpentieri , Zhaoli Shen , Tingzhu Huang

In this paper, a well-posed simultaneous space-time First Order System Least Squares formulation is constructed of the instationary incompressible Stokes equations with slip boundary conditions. As a consequence of this well-posedness, the…

Numerical Analysis · Mathematics 2022-08-24 Gregor Gantner , Rob Stevenson

Complex valued systems with an indefinite matrix term arise in important applications such as for certain time-harmonic partial differential equations such as the Maxwell's equation and for the Helmholtz equation. Complex systems with…

Numerical Analysis · Mathematics 2021-10-04 Owe Axelsson , Maeddeh Pourbagher , Davod Khojasteh Salkuyeh

In this article, we propose and study a stochastic and relaxed preconditioned Douglas--Rachford splitting method to solve saddle-point problems that have separable dual variables. We prove the almost sure convergence of the iteration…

Optimization and Control · Mathematics 2024-10-01 Yakun Dong , Kristian Bredies , Hongpeng Sun
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