Nowadays, analysis and design of novel scalable methods and algorithms for fundamental linear algebra problems such as solving Systems of Linear Algebraic Equations with focus on large scale systems is a subject of study. This research focuses on the study of novel mathematical methods and scalable algorithms for computationally intensive problems such as Monte Carlo and Hybrid Methods and Algorithms
When simulating a mechanism from science or engineering, or an industrial process, one is frequently...
Cette thèse traite d’une nouvelle classe de préconditionneurs qui ont pour but d’accélérer la résolu...
In this paper we introduce a new algorithm, based on the successful work of Fathi and Alexandrov, on...
Many problems in science and engineering can be represented by Systems of Linear Algebraic Equations...
AbstractAn enhanced version of a stochastic SParse Approximate Inverse (SPAI) preconditioner for gen...
Abstract. The problem of solving sparse Systems of Linear Algebraic Equations (SLAE) by parallel Mon...
International audienceA new Walk on Equations (WE) Monte Carlo algorithm for Linear Algebra (LA) pro...
AbstractIn this paper we present a stochastic SPAI pre-conditioner. In contrast to the standard dete...
We describe a new Monte Carlo method based on a multilevel method for computing the action of the re...
AbstractA new parallel algorithm for the solution of linear systems, based upon the Monte Carlo appr...
This article surveys preconditioning techniques for the iterative solution of large linear systems, ...
Linear algebra operations play an important role in scientific computing and data analysis. With inc...
We consider hybrid deterministic-stochastic iterative algorithms for the solution of large, sparse l...
The problem of solving System of Linear Algebraic Equations (SLAE) by parallel Monte Carlo numerical...
We review current methods for preconditioning systems of equations for their solution using iterativ...
When simulating a mechanism from science or engineering, or an industrial process, one is frequently...
Cette thèse traite d’une nouvelle classe de préconditionneurs qui ont pour but d’accélérer la résolu...
In this paper we introduce a new algorithm, based on the successful work of Fathi and Alexandrov, on...
Many problems in science and engineering can be represented by Systems of Linear Algebraic Equations...
AbstractAn enhanced version of a stochastic SParse Approximate Inverse (SPAI) preconditioner for gen...
Abstract. The problem of solving sparse Systems of Linear Algebraic Equations (SLAE) by parallel Mon...
International audienceA new Walk on Equations (WE) Monte Carlo algorithm for Linear Algebra (LA) pro...
AbstractIn this paper we present a stochastic SPAI pre-conditioner. In contrast to the standard dete...
We describe a new Monte Carlo method based on a multilevel method for computing the action of the re...
AbstractA new parallel algorithm for the solution of linear systems, based upon the Monte Carlo appr...
This article surveys preconditioning techniques for the iterative solution of large linear systems, ...
Linear algebra operations play an important role in scientific computing and data analysis. With inc...
We consider hybrid deterministic-stochastic iterative algorithms for the solution of large, sparse l...
The problem of solving System of Linear Algebraic Equations (SLAE) by parallel Monte Carlo numerical...
We review current methods for preconditioning systems of equations for their solution using iterativ...
When simulating a mechanism from science or engineering, or an industrial process, one is frequently...
Cette thèse traite d’une nouvelle classe de préconditionneurs qui ont pour but d’accélérer la résolu...
In this paper we introduce a new algorithm, based on the successful work of Fathi and Alexandrov, on...