We introduce a class of preconditioners for general sparse matrices based on the Birkhoff-von Neumann decomposition of doubly stochastic matrices. These preconditioners are aimed primarily at solving challenging linear systems with highly unstructured and indefinite coefficient matrices. We present some theoretical results and numerical experiments on linear systems from a variety of applications
AbstractThis paper presents a class of preconditioning techniques which exploit rational function ap...
After briefly recalling some relevant approaches for preconditioning large symmetric linear systems,...
For the large sparse block two-by-two real nonsingular matrices, we establish a general framework of...
International audienceWe introduce a class of preconditioners for general sparse matrices based on t...
AbstractA new sparse approximate triangular factorization technique for solving large sparse linear ...
This article surveys preconditioning techniques for the iterative solution of large linear systems, ...
Our weakly random additive preconditioners facilitate the solution of linear systems of equa-tions a...
Iterative methods are currently the solvers of choice for large sparse linear systems of equations. ...
Standard preconditioners, like incomplete factorizations, perform well when the coefficient matrix i...
Versus the customary preconditioners, our weakly random ones are generated more readily and for a mu...
. This paper is concerned with a new approach to preconditioning for large, sparse linear systems. A...
This paper is concerned with a new approach to preconditioning for large, sparse linear systems. A p...
This thesis deals with the construction of preconditioners for systems of linear equations as they o...
By considering Krylov subspace methods in nonstandard inner products, we develop in this thesis new ...
After briefly recalling some relevant approaches for preconditioning large symmetric linear systems,...
AbstractThis paper presents a class of preconditioning techniques which exploit rational function ap...
After briefly recalling some relevant approaches for preconditioning large symmetric linear systems,...
For the large sparse block two-by-two real nonsingular matrices, we establish a general framework of...
International audienceWe introduce a class of preconditioners for general sparse matrices based on t...
AbstractA new sparse approximate triangular factorization technique for solving large sparse linear ...
This article surveys preconditioning techniques for the iterative solution of large linear systems, ...
Our weakly random additive preconditioners facilitate the solution of linear systems of equa-tions a...
Iterative methods are currently the solvers of choice for large sparse linear systems of equations. ...
Standard preconditioners, like incomplete factorizations, perform well when the coefficient matrix i...
Versus the customary preconditioners, our weakly random ones are generated more readily and for a mu...
. This paper is concerned with a new approach to preconditioning for large, sparse linear systems. A...
This paper is concerned with a new approach to preconditioning for large, sparse linear systems. A p...
This thesis deals with the construction of preconditioners for systems of linear equations as they o...
By considering Krylov subspace methods in nonstandard inner products, we develop in this thesis new ...
After briefly recalling some relevant approaches for preconditioning large symmetric linear systems,...
AbstractThis paper presents a class of preconditioning techniques which exploit rational function ap...
After briefly recalling some relevant approaches for preconditioning large symmetric linear systems,...
For the large sparse block two-by-two real nonsingular matrices, we establish a general framework of...