Reproducibility in Matrix and Tensor Decompositions: Focus on model match, interpretability, and uniqueness
- DOI
- 10.1109/msp.2022.3163870
- Published
- 2022-07
- Container
- IEEE Signal Processing Magazine
- Publisher
- Institute of Electrical and Electronics Engineers (IEEE)
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1109/msp.2022.3163870,
title = {Reproducibility in Matrix and Tensor Decompositions: Focus on model match, interpretability, and uniqueness},
author = {Tulay Adali and Furkan Kantar and Mohammad Abu Baker Siddique Akhonda and Stephen Strother and Vince D. Calhoun and Evrim Acar},
year = {2022},
journal = {IEEE Signal Processing Magazine},
doi = {10.1109/msp.2022.3163870},
url = {https://doi.org/10.1109/msp.2022.3163870}
}RIS
TY - JOUR TI - Reproducibility in Matrix and Tensor Decompositions: Focus on model match, interpretability, and uniqueness AU - Tulay Adali AU - Furkan Kantar AU - Mohammad Abu Baker Siddique Akhonda AU - Stephen Strother AU - Vince D. Calhoun AU - Evrim Acar PY - 2022 JO - IEEE Signal Processing Magazine DO - 10.1109/msp.2022.3163870 UR - https://doi.org/10.1109/msp.2022.3163870 ER -
APA
Adali, T., Kantar, F., Akhonda, M. A. B. S., Strother, S., Calhoun, V. D., & Acar, E. (2022). Reproducibility in Matrix and Tensor Decompositions: Focus on model match, interpretability, and uniqueness. IEEE Signal Processing Magazine. https://doi.org/10.1109/msp.2022.3163870
Source records
- crossref · retrieved 2026-09-25T12:27:32.721Z