Low-Rank Tensor Methods with Subspace Correction for Symmetric Eigenvalue Problems

DOI10.1137/130949919zbMath1307.65040OpenAlexW2008657736MaRDI QIDQ2940012

Daniel Kressner, André Uschmajew, Michael Steinlechner

Publication date: 23 January 2015

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

Full work available at URL: https://doi.org/10.1137/130949919

zbMATH Keywords

preconditioningnumerical experimenttensor train formattrace minimizationlow-rank tensor methodshigh-dimensional eigenvalue problems

Mathematics Subject Classification ID

Numerical computation of eigenvalues and eigenvectors of matrices (65F15) Numerical methods for eigenvalue problems for boundary value problems involving PDEs (65N25) Preconditioners for iterative methods (65F08)

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