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Proceedings Paper

Robust decomposition of 3-way tensors based on L1-norm
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Paper Abstract

Rank-1 L1-norm-based TUCKER2 (L1-TUCKER2) decomposition of 3-way tensors was recently solved exactly, for the first time, by Markopoulos et al.1 The exact solution to general-rank L1-TUCKER2 remains to date unknown. In this work, we present a novel approximate algorithm for general-rank L1-TUCKER2 decomposition of 3-way tensors. Our algorithm is accompanied by formal convergence and complexity analysis. Our numerical studies illustrate the sturdy corruption resistance of the proposed algorithm compared to state-of-the-art TUCKER2-decomposition counterparts such as GLRAM, HOSVD, and HOOI.

Paper Details

Date Published: 14 May 2018
PDF: 15 pages
Proc. SPIE 10658, Compressive Sensing VII: From Diverse Modalities to Big Data Analytics, 1065807 (14 May 2018); doi: 10.1117/12.2307843
Show Author Affiliations
Dimitris G. Chachlakis, Rochester Institute of Technology (United States)
Panos P. Markopoulos, Rochester Institute of Technology (United States)

Published in SPIE Proceedings Vol. 10658:
Compressive Sensing VII: From Diverse Modalities to Big Data Analytics
Fauzia Ahmad, Editor(s)

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