This paper provides an overview of AMG methods for solving large-scale systems of
equations, such as those from discretizations of partial differential equations. AMG is often …

We introduce a coarsening algorithm for algebraic multigrid (AMG) based on the concept of
compatible relaxation (CR). The algorithm is significantly different from standard methods …

This paper provides a unified and detailed presentation of root-node--style algebraic
multigrid (AMG). AMG is a popular and effective iterative method for solving large, sparse …

The computational complexity of solving nonlinear support vector machine (SVM) is
prohibitive on large-scale data. In particular, this issue becomes very sensitive when the …

AMG is one of the most efficient and widely used methods for solving sparse linear systems.
The computational process of AMG mainly consists of a series of iterative calculations of …

Multilevel techniques are efficient approaches for solving the large linear systems that arise
from discretized partial differential equations and other problems. While geometric multigrid …

We present a novel deep learning-based algorithm to accelerate—through the use of
Artificial Neural Networks (ANNs)—the convergence of Algebraic Multigrid (AMG) methods …

A new prolongator is proposed for smoothed aggregation (SA) multigrid. The proposed
prolongator addresses a limitation of standard SA when it is applied to anisotropic problems …

A multigrid method is proposed that combines ideas from matrix dependent multigrid for
structured grids and algebraic multigrid for unstructured grids. It targets problems where a …

In the mathematical modeling of real-life applications, systems of equations with complex
coefficients often arise. While many techniques of numerical linear algebra, eg, Krylov …