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Algebraic PGD for tensor separation and compression: an algorithmic approach

Author
Diez, P.; Zlotnik, S.; Garcia, A.; Huerta, A.
Type of activity
Journal article
Journal
Comptes rendus mécanique
Date of publication
2018-07
Volume
346
Number
7
First page
501
Last page
514
DOI
https://doi.org/10.1016/j.crme.2018.04.011 Open in new window
Repository
http://hdl.handle.net/2117/123592 Open in new window
URL
https://www.sciencedirect.com/science/article/pii/S1631072118300809 Open in new window
Abstract
Proper Generalized Decomposition (PGD) is devised as a computational method to solve high-dimensional boundary value problems (where many dimensions are associated with the space of parameters defining the problem). The PGD philosophy consists in providing a separated representation of the multidimensional solution using a greedy approach combined with an alternated directions scheme to obtain the successive rank-one terms. This paper presents an algorithmic approach to high-dimensional tensor s...
Citation
Diez, P., Zlotnik, S., Garcia, A., Huerta, A. Algebraic PGD for tensor separation and compression: an algorithmic approach. "Comptes rendus mécanique", Juliol 2018, vol. 346, núm. 7, p. 501-514.
Keywords
Algebraic PGD, Least-squares approximation, Tensor separation
Group of research
LACÀN - Numerical Methods for Applied Sciences and Engineering

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