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A new primal-dual weak Galerkin (PD-WG) finite element method was developed and analyzed in this article for first-order linear convection equations in non-divergence form. The PD-WG method results in a symmetric discrete system involving…

Numerical Analysis · Mathematics 2019-11-20 Dan Li , Chunmei Wang , Junping Wang

The local and overall responses of nonlinear composites are classically investigated by the Finite Element Method. We propose an alternate method based on Fourier series which avoids meshing and which makes direct use of microstructure…

Computational Engineering, Finance, and Science · Computer Science 2020-12-17 H. Moulinec , Pierre Suquet

Inversion of sparse matrices with standard direct solve schemes is robust, but computationally expensive. Iterative solvers, on the other hand, demonstrate better scalability; but, need to be used with an appropriate preconditioner (e.g.,…

Numerical Analysis · Mathematics 2017-09-28 Hadi Pouransari , Pieter Coulier , Eric Darve

In this paper, we propose three methods to solve the PageRank problem for the transition matrices with both row and column sparsity. Our methods reduce the PageRank problem to the convex optimization problem over the simplex. The first…

Optimization and Control · Mathematics 2020-12-22 Anton Anikin , Alexander Gasnikov , Alexander Gornov , Dmitry Kamzolov , Yury Maximov , Yurii Nesterov

We investigate the use of piecewise linear systems, whose coefficient matrix is a piecewise constant function of the solution itself. Such systems arise, for example, from the numerical solution of linear complementarity problems and in the…

Numerical Analysis · Mathematics 2012-06-21 Luigi Brugnano , Alessandra Sestini

We consider a standard federated learning (FL) architecture where a group of clients periodically coordinate with a central server to train a statistical model. We develop a general algorithmic framework called FedLin to tackle some of the…

Machine Learning · Computer Science 2021-09-01 Aritra Mitra , Rayana Jaafar , George J. Pappas , Hamed Hassani

There is growing interest in learning Fourier domain sampling strategies (particularly for magnetic resonance imaging, MRI) using optimization approaches. For non-Cartesian sampling patterns, the system models typically involve non-uniform…

Image and Video Processing · Electrical Eng. & Systems 2023-02-07 Guanhua Wang , Jeffrey A. Fessler

Iterative algorithms are instrumental in modern numerical simulation for solving systems arising from the discretization of PDEs. They face however significant challenges in industrial applications, such as slow convergence, limit cycle…

Numerical Analysis · Mathematics 2026-05-05 Jeremy Kalfoun , Guillaume Pierrot , John Cagnol

In this work we introduce and analyze a new multiscale method for strongly nonlinear monotone equations in the spirit of the Localized Orthogonal Decomposition. A problem-adapted multiscale space is constructed by solving linear local…

Numerical Analysis · Mathematics 2020-12-16 Barbara Verfürth

Nonlinear least-squares problems are a special class of unconstrained optimization problems in which their gradient and Hessian have special structures. In this paper, we exploit these structures and proposed a matrix-free algorithm with a…

Optimization and Control · Mathematics 2020-02-06 Aliyu Muhammed Awwal , Poom Kumam , Hassan Mohammad

We design and investigate efficient multigrid solvers for multiphase Stokes problems discretised via mixed-degree local discontinuous Galerkin methods. Using the template of a standard multigrid V-cycle, we develop a smoother analogous to…

Numerical Analysis · Mathematics 2025-11-26 Robert I. Saye

This article presents a new primal-dual weak Galerkin method for second order elliptic equations in non-divergence form. The new method is devised as a constrained $L^p$-optimization problem with constraints that mimic the second order…

Numerical Analysis · Mathematics 2021-06-08 Waixiang Cao , Junping Wang , Yuesheng Xu

Randomized iterative algorithms have attracted much attention in recent years because they can approximately solve large-scale linear systems of equations without accessing the entire coefficient matrix. In this paper, we propose two novel…

Numerical Analysis · Mathematics 2021-10-22 Kui Du , Xiao-Hui Sun

A coupled hybridizable discontinuous Galerkin (HDG) and boundary integral (BI) method is proposed to efficiently analyze electromagnetic scattering from inhomogeneous/composite objects. The coupling between the HDG and the BI equations is…

Computational Engineering, Finance, and Science · Computer Science 2023-06-21 Ran Zhao , Ming Dong , Liang Chen , Jun Hu , Hakan Bagci

Regularized nonnegative low-rank approximations, such as sparse Nonnegative Matrix Factorization or sparse Nonnegative Tucker Decomposition, form an important branch of dimensionality reduction models known for their enhanced…

Machine Learning · Computer Science 2025-01-31 Jeremy E. Cohen , Valentin Leplat

We present a fast spectral Galerkin scheme for the discretization of boundary integral equations arising from two-dimensional Helmholtz transmission problems in multi-layered periodic structures or gratings. Employing suitably parametrized…

Numerical Analysis · Mathematics 2020-11-06 José Pinto , Rubén Aylwin , Carlos Jerez-Hanckes

Recent development on mixed precision techniques has largely enhanced the performance of various linear algebra solvers, one of which being the solver for the least squares problem $\min_{x}\lVert b-Ax\rVert_{2}$. By transforming least…

Numerical Analysis · Mathematics 2025-09-09 Bowen Gao , Yuxin Ma , Meiyue Shao

The high-order hybridizable discontinuous Galerkin (HDG) method combining with an implicit iterative scheme is used to find the steady-state solution of the Boltzmann equation with full collision integral on two-dimensional triangular…

Fluid Dynamics · Physics 2020-02-19 Wei Su , Peng Wang , Yonghao Zhang , Lei Wu

The paper starts out with a computational technique that allows to compare all linear methods for PDE solving that use the same input data. This is done by writing them as linear recovery formulas for solution values as linear combinations…

Numerical Analysis · Mathematics 2013-02-13 Robert Schaback

Large linear systems with sparse, non-symmetric matrices arise in the modeling of Markov chains or in the discretization of convection-diffusion problems. Due to their potential to solve sparse linear systems with an effort that is linear…

Numerical Analysis · Mathematics 2023-08-17 Benjamin Seibold