An Adaptive Algebraic Multigrid Algorithm for Low-Rank Canonical Tensor Decomposition

DOI10.1137/110855934zbMath1264.65045arXiv1111.6091OpenAlexW2018014435MaRDI QIDQ4917148

Killian Miller, Hans De Sterck

Publication date: 29 April 2013

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

Full work available at URL: https://arxiv.org/abs/1111.6091

zbMATH Keywords

algorithmnumerical examplesalgebraic multigridmultilevel methodalternating least squaresCANDECOMPPARAFACcanonical tensor decompositionnumerical multilinear algebra

Mathematics Subject Classification ID

Numerical solutions to overdetermined systems, pseudoinverses (65F20) Iterative numerical methods for linear systems (65F10) Multilinear algebra, tensor calculus (15A69)

Related Items (9)

Enhanced alternating energy minimization methods for stochastic Galerkin matrix equations ⋮ A Derivative-Free Nonlinear Least Squares Solver ⋮ A Riemannian Trust Region Method for the Canonical Tensor Rank Approximation Problem ⋮ Ideal minimal residual-based proper generalized decomposition for non-symmetric multi-field models -- application to transient elastodynamics in space-time domain ⋮ Range-Separated Tensor Format for Many-Particle Modeling ⋮ On the Asymptotic Linear Convergence Speed of Anderson Acceleration, Nesterov Acceleration, and Nonlinear GMRES ⋮ Greedy low-rank approximation in Tucker format of solutions of tensor linear systems ⋮ Multigrid Methods for Tensor Structured Markov Chains with Low Rank Approximation ⋮ The Dynamics of Swamps in the Canonical Tensor Approximation Problem

Uses Software

• TensorToolbox

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