On efficient Monte Carlo preconditioners and hybrid Monte Carlo methods for linear algebra
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ACM Press
Reference25 articles.
1. V. Alexandrov, E. Atanassov, I. Dimov, S. Branford, A. Thandavan, and C. Weihrauch. Parallel Hybrid Monte Carlo Algorithms for Matrix Computations. In V. Sunderam, editor,Computational Science -- ICCS 2005, volume 3516 ofLecture Notes in Computer Science, pages 752--759. Springer Berlin / Heidelberg, 2005.
2. V. Alexandrov and O. Esquivel-Flores. Towards Monte Carlo Preconditioning Approach and Hybrid Monte Carlo Algorithms for Matrix Computations.Computers and Mathematics with Applications, (in publication), 2015.
3. V. Alexandrov and A. Karaivanova. Parallel Monte Carlo algorithms for sparse SLAE using MPI. InRecent Advances in Parallel Virtual Machine and Message Passing Interface, pages 283--290. Springer, 1999.
4. G. Alléon, M. Benzi, and L. Giraud. Sparse approximate inverse preconditioning for dense linear systems arising in computational electromagnetics.Numerical Algorithms, 16(1):1--15, 1997.
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