Randomized Alternating Least Squares for Canonical Tensor Decompositions: Application to A PDE With Random Data

DOI10.1137/15M1042802zbMath1348.65012arXiv1510.01398OpenAlexW2964341462MaRDI QIDQ2818256

Alireza Doostan, Matthew J. Reynolds, Gregory Beylkin

Publication date: 7 September 2016

Published in: SIAM Journal on Scientific Computing (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1510.01398

zbMATH Keywords

algorithmnumerical examplescondition numbertensor decompositionalternating least squaresrank reductionseparated representationsstochastic PDErandomized projectioncanonical tensorsoverdetermined least squares problems

Mathematics Subject Classification ID

Numerical solutions to overdetermined systems, pseudoinverses (65F20) Stochastic partial differential equations (aspects of stochastic analysis) (60H15) PDEs with randomness, stochastic partial differential equations (35R60) Computational methods for stochastic equations (aspects of stochastic analysis) (60H35) Numerical solutions to stochastic differential and integral equations (65C30)

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Uses Software

• PARAFAC

Cites Work

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