Vigneron, Vincent and Kodewitz, Andreas and da Costa, Michele Nazareth and Tome, Ana Maria and Lang, Elmar (2018) Non-negative sub-tensor ensemble factorization (NsTEF) algorithm. A new incremental tensor factorization for large data sets. SIGNAL PROCESSING, 144. pp. 77-86. ISSN 0165-1684, 1879-2677
Full text not available from this repository. (Request a copy)Abstract
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.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | MATRIX FACTORIZATION; CANONICAL DECOMPOSITION; UNIQUENESS; CANDECOMP/PARAFAC; CLASSIFICATION; RECOGNITION; MODE; Non-negative tensor decomposition; CANDECOMP/PARAFAC Decomposition; Matrix factorization; NTF; Incremental algorithm; Learning method |
| Subjects: | 500 Science > 570 Life sciences |
| Divisions: | Biology, Preclinical Medicine > Institut für Biophysik und physikalische Biochemie > Prof. Dr. Elmar Lang |
| Depositing User: | Dr. Gernot Deinzer |
| Date Deposited: | 19 Mar 2020 09:58 |
| Last Modified: | 19 Mar 2020 09:58 |
| URI: | https://pred.uni-regensburg.de/id/eprint/14935 |
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