Multigrid methods combined with low-rank approximation for tensor-structured Markov chains

DOI10.1553/etna_vol48s348zbMath1401.65031arXiv1605.06246OpenAlexW2963257358WikidataQ129116841 ScholiaQ129116841MaRDI QIDQ1990903

Sonja Sokolović, Francisco Macedo, Karsten Kahl, Daniel Kressner, Matthias Bolten

Publication date: 26 October 2018

Published in: ETNA. Electronic Transactions on Numerical Analysis (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1605.06246

zbMATH Keywords

Markov chainsmultigrid methodSVDtensor train formatalternating optimizationsingular linear system

Mathematics Subject Classification ID

Computational methods in Markov chains (60J22) Computational methods for sparse matrices (65F50) Multigrid methods; domain decomposition for boundary value problems involving PDEs (65N55) Iterative numerical methods for linear systems (65F10) Multilinear algebra, tensor calculus (15A69)

Related Items (1)

Low-rank tensor methods for Markov chains with applications to tumor progression models

Uses Software

• Matlab

Cites Work

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