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

Dimitris G. Chachlakis; Panos P. Markopoulos

doi:10.1117/12.2307843

14 May 2018 Robust decomposition of 3-way tensors based on L1-norm

Dimitris G. Chachlakis, Panos P. Markopoulos

Proceedings Volume 10658, Compressive Sensing VII: From Diverse Modalities to Big Data Analytics; 1065807 (2018) https://doi.org/10.1117/12.2307843
Event: SPIE Commercial + Scientific Sensing and Imaging, 2018, Orlando, FL, United States

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.

Citation Download Citation

Dimitris G. Chachlakis and Panos P. Markopoulos "Robust decomposition of 3-way tensors based on L1-norm", Proc. SPIE 10658, Compressive Sensing VII: From Diverse Modalities to Big Data Analytics, 1065807 (14 May 2018); https://doi.org/10.1117/12.2307843

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