Linear convergence of an alternating polar decomposition method for low rank orthogonal tensor approximations

Abstract Low rank orthogonal tensor approximation (LROTA) is an important problem in tensor computations and their applications. A classical and widely used algorithm is the alternating polar decomposition method (APD). In this paper, an improved version iAPD of the classical APD is proposed. For th...
Ausführliche Beschreibung

Gespeichert in:
Autor*in:

Hu, Shenglong [verfasserIn]

Ye, Ke

Format:

E-Artikel

Sprache:

Englisch

Erschienen:

2022

Schlagwörter:

Orthogonally decomposable tensors

Low rank orthogonal tensor approximation

-linear convergence

Sublinear convergence

Global convergence

Anmerkung:

© Springer-Verlag GmbH Germany, part of Springer Nature and Mathematical Optimization Society 2022. Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Übergeordnetes Werk:

Enthalten in: Mathematical programming - Berlin : Springer, 1971, 199(2022), 1-2 vom: 30. Juli, Seite 1305-1364

Übergeordnetes Werk:

volume:199 ; year:2022 ; number:1-2 ; day:30 ; month:07 ; pages:1305-1364

Links:

Volltext

DOI / URN:

10.1007/s10107-022-01867-8

Katalog-ID:

SPR050132830

Nicht das Richtige dabei?

Schreiben Sie uns!