5 citations · 12 across the 6 of their papers we have counts for
7 papers
Accelerating a restarted Krylov method for matrix functions with randomization
Nicolas L. Guidotti, Per-Gunnar Martinsson, Juan A. Acebrón +1
Many scientific applications require the evaluation of the action of a matrix function on a vector, and Krylov subspace methods are the most common ones for this task. Since the or…
Sensitivity analysis of fractional linear systems based on random walks with negligible memory usage
Andrés Centeno, Juan A. Acebrón, José Monteiro
A random walk-based method is proposed to efficiently compute the solution of a large class of fractional in time linear systems of differential equations (linear F-ODE systems), a…
Parallelization Strategies for the Randomized Kaczmarz Algorithm on Large-Scale Dense Systems
Inês Ferreira, Juan A. Acebrón, José Monteiro
The Kaczmarz algorithm is an iterative technique designed to solve consistent linear systems of equations. It falls within the category of row-action methods, focusing on handling…
Survey of a Class of Iterative Row-Action Methods: The Kaczmarz Method
Inês A. Ferreira, Juan A. Acebrón, José Monteiro
The Kaczmarz algorithm is an iterative method that solves linear systems of equations. It stands out among iterative algorithms when dealing with large systems for two reasons. Fir…
A Fast Monte Carlo algorithm for evaluating matrix functions with application in complex networks
Nicolas L. Guidotti, Juan A. Acebrón, José Monteiro
We propose a novel stochastic algorithm that randomly samples entire rows and columns of the matrix as a way to approximate an arbitrary matrix function using the power series expa…
A Stochastic Method for Solving Time-Fractional Differential Equations
Nicolas L. Guidotti, Juan Acebrón, José Monteiro
We present a stochastic method for efficiently computing the solution of time-fractional partial differential equations (fPDEs) that model anomalous diffusion problems of the subdi…
A hybrid probabilistic domain decomposition algorithm suited for very large-scale elliptic PDEs
Francisco Bernal, Jorge Morón-Vidal, Juan A. Acebrón
State of the art domain decomposition algorithms for large-scale boundary value problems (with degrees of freedom) suffer from bounded strong scalability because they invo…