Non-negative sub-tensor ensemble factorization (NsTEF) algorithm. A new incremental tensor factorization for large data sets.
- DOI
- 10.1016/j.sigpro.2017.09.012
- Published
- 2018-03
- Container
- Signal Processing
- Publisher
- Elsevier BV
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1016/j.sigpro.2017.09.012,
title = {Non-negative sub-tensor ensemble factorization (NsTEF) algorithm. A new incremental tensor factorization for large data sets.},
author = {Vincent Vigneron and Andreas Kodewitz and Michele Nazareth da Costa and Ana Maria Tome and Elmar Langlang},
year = {2018},
journal = {Signal Processing},
doi = {10.1016/j.sigpro.2017.09.012},
url = {https://doi.org/10.1016/j.sigpro.2017.09.012}
}RIS
TY - JOUR TI - Non-negative sub-tensor ensemble factorization (NsTEF) algorithm. A new incremental tensor factorization for large data sets. AU - Vincent Vigneron AU - Andreas Kodewitz AU - Michele Nazareth da Costa AU - Ana Maria Tome AU - Elmar Langlang PY - 2018 JO - Signal Processing DO - 10.1016/j.sigpro.2017.09.012 UR - https://doi.org/10.1016/j.sigpro.2017.09.012 ER -
APA
Vigneron, V., Kodewitz, A., Costa, M. N. D., Tome, A. M., & Langlang, E. (2018). Non-negative sub-tensor ensemble factorization (NsTEF) algorithm. A new incremental tensor factorization for large data sets.. Signal Processing. https://doi.org/10.1016/j.sigpro.2017.09.012
Source records
- crossref · retrieved 2026-09-25T11:39:59.550Z