Iterative Methods Based on Soft Thresholding of Hierarchical Tensors

Iterative Methods Based on Soft Thresholding of Hierarchical Tensors We construct a soft thresholding operation for rank reduction in hierarchical tensors and subsequently consider its use in iterative thresholding methods, in particular for the solution of discretized high-dimensional elliptic problems. The proposed method for the latter case adjusts the thresholding parameters, by an a posteriori criterion requiring only bounds on the spectrum of the operator, such that the arising tensor ranks of the resulting iterates remain quasi-optimal with respect to the algebraic or exponential-type decay of the hierarchical singular values of the true solution. In addition, we give a modified algorithm using inexactly evaluated residuals that retains these features. The effectiveness of the scheme is demonstrated in numerical experiments. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Foundations of Computational Mathematics Springer Journals

Iterative Methods Based on Soft Thresholding of Hierarchical Tensors

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Publisher
Springer US
Copyright
Copyright © 2016 by SFoCM
Subject
Mathematics; Numerical Analysis; Economics, general; Applications of Mathematics; Linear and Multilinear Algebras, Matrix Theory; Math Applications in Computer Science; Computer Science, general
ISSN
1615-3375
eISSN
1615-3383
D.O.I.
10.1007/s10208-016-9314-z
Publisher site
See Article on Publisher Site

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