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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Non-negative sub-tensor ensemble factorization (NsTEF) algorithm. A new incremental tensor factorization for large data sets

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Vigneron, Vincent [1] ; Kodewitz, Andreas [1] ; da Costa, Michele Nazareth [2] ; Tome, Ana Maria [3] ; Langlang, Elmar [4]
Total Authors: 5
[1] Univ Paris Saclay, Univ Ewy, IBISC, F-91025 Evry - France
[2] Univ Campinas UNICAMP, DSPCom Lab, POB 6101, BR-13083852 Campinas, SP - Brazil
[3] Univ Aveiro, Dept Elect Telecomunicacoes & Informat, Aveiro - Portugal
[4] Univ Regensburg, Inst Biophys & Phys Biochem, Univ Str 31, D-93040 Regensburg - Germany
Total Affiliations: 4
Document type: Journal article
Source: Signal Processing; v. 144, p. 77-86, MAR 2018.
Web of Science Citations: 1

In this work we present a novel algorithm for nonnegative tensor factorization (NTF). Standard NTF algorithms are very restricted in the size of tensors that can be decomposed. Our algorithm overcomes this size restriction by interpreting the tensor as a set of sub-tensors and by proceeding the decomposition of sub-tensor by sub-tensor. This approach requires only one sub-tensor at once to be available in memory. (C) 2017 Elsevier B.V. All rights reserved. (AU)

FAPESP's process: 14/23936-4 - Applications of multidimensional data processing using tensor methods
Grantee:Michele Nazareth da Costa
Support Opportunities: Scholarships in Brazil - Post-Doctoral