Wilkinson defined a sparse matrix as one with enough zeros that it pays to take advantage of
them. 1 This informal yet practical definition captures the essence of the goal of direct …

This textbook covers both direct and iterative methods for the solution of linear systems, least
squares problems, eigenproblems, and the singular value decomposition. Earlier versions …

This paper introduces a new efficient algorithm for computing Gröbner bases. To avoid as
much intermediate computation as possible, the algorithm computes successive truncated …

Discretization of linear inverse problems generally gives rise to very ill-conditioned linear
systems of algebraic equations. Typically, the linear systems obtained have to be …

The purpose of this book is to unify and document in one place many of the techniques and
much of the current understanding about solving systems of linear equations on vector and …

In this review paper, we consider some important developments and trends in algorithm
design for the solution of linear systems concentrating on aspects that involve the …

This is the first text explaining how to use the bulk synchronous parallel (BSP) model and the
freely available BSPlib communication library in parallel algorithm design and parallel …

We study the approach to obtaining least squares solutions to systems of linear algebraic
equations over networks by using distributed algorithms. Each node has access to one of …

{\footnotesize In der vorliegenden Arbeit werden neue Implementierungen des dualen und
primalen revidierten Simplex-Algorithmus für die Lösung linearer Programme (LPs) …

This article deals with linear equations of the form. By reformulating the original problem as
an unconstrained optimization problem, we first provide a gradient-based distributed …