Coherence Constrained Alternating Least Squares
Autor: | Rodrigo Cabral Farias, Pierre Comon, José Henrique de Morais Goulart |
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Přispěvatelé: | Laboratoire d'Informatique, Signaux, et Systèmes de Sophia-Antipolis (I3S) / Equipe SYSTEMES, Signal, Images et Systèmes (Laboratoire I3S - SIS), Laboratoire d'Informatique, Signaux, et Systèmes de Sophia Antipolis (I3S), Université Nice Sophia Antipolis (... - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UCA)-Université Nice Sophia Antipolis (... - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UCA)-Laboratoire d'Informatique, Signaux, et Systèmes de Sophia Antipolis (I3S), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UCA), GIPSA - Communication Information and Complex Systems (GIPSA-CICS), Département Images et Signal (GIPSA-DIS), Grenoble Images Parole Signal Automatique (GIPSA-lab ), Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Grenoble Images Parole Signal Automatique (GIPSA-lab ), Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), European Project: 320594,EC:FP7:ERC,ERC-2012-ADG_20120216,DECODA(2013), Université Nice Sophia Antipolis (1965 - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UCA)-Université Nice Sophia Antipolis (1965 - 2019) (UNS) |
Rok vydání: | 2018 |
Předmět: |
Mutual coherence
Computer science Degenerate energy levels MathematicsofComputing_NUMERICALANALYSIS Approximation algorithm Initialization 020206 networking & telecommunications 010103 numerical & computational mathematics 02 engineering and technology 01 natural sciences Matrix decomposition [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing Iterated function 0202 electrical engineering electronic engineering information engineering Applied mathematics Coherence (signal processing) Tensor 0101 mathematics |
Zdroj: | EUSIPCO EUSIPCO 2018-26th European Signal Processing Conference EUSIPCO 2018-26th European Signal Processing Conference, Sep 2018, Rome, Italy. ⟨10.23919/EUSIPCO.2018.8553084⟩ |
Popis: | International audience; In this paper we present a modification of alternating least squares (ALS) for tensor canonical polyadic approximation that takes into account mutual coherence constraints. The proposed algorithm can be used to ensure well-posedness of the tensor approximation problem during ALS iterates and so is an alternative to existing approaches. We conduct tests with the proposed approach by using it as initialization of unconstrained alternating least squares in difficult cases, when the underlying tensor model factors have nearly collinear columns and the unconstrained approach is prone to a degenerate behavior, failing to converge or converging slowly to an acceptable solution. The results of the tested cases indicate that by using such an initialization the unconstrained approach seems to avoid such a behavior. |
Databáze: | OpenAIRE |
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