Vector Monte Carlo stochastic matrix-based algorithms for large linear systems

DOI10.1515/mcma-2016-0112zbMath1347.65007OpenAlexW2515212664MaRDI QIDQ308409

K. K. Sabel'fel'd

Publication date: 6 September 2016

Published in: Monte Carlo Methods and Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1515/mcma-2016-0112

zbMATH Keywords

balancingstochastic matrixdouble stochastic matricesrandom gradient

Mathematics Subject Classification ID

Monte Carlo methods (65C05) Numerical analysis or methods applied to Markov chains (65C40) Applications to the sciences (65Z05)

Related Items (1)

Randomized vector iterative linear solvers of high precision for large dense system

Cites Work

• Unnamed Item
• Unnamed Item
• Sparsified randomization algorithms for low rank approximations and applications to integral equations and inhomogeneous random field simulation
• The rate of convergence of Sinkhorn balancing
• A randomized Kaczmarz algorithm with exponential convergence
• Matrix scaling: A geometric proof of Sinkhorn's theorem
• Concerning nonnegative matrices and doubly stochastic matrices
• Stochastic iterative projection methods for large linear systems
• Stochastic Algorithms in Linear Algebra - beyond the Markov Chains and von Neumann - Ulam Scheme
• Stochastic Methods for Boundary Value Problems
• Exponential bounds for the probability deviations of sums of random fields
• Sparsified Randomization Algorithms for large systems of linear equations and a new version of the Random Walk on Boundary method
• Using Randomization to Break the Curse of Dimensionality
• A Relationship Between Arbitrary Positive Matrices and Doubly Stochastic Matrices

This page was built for publication: Vector Monte Carlo stochastic matrix-based algorithms for large linear systems