An optimal pairwise merge algorithm improves the quality and consistency of nonnegative matrix factorization.

Guo Y, Holy TE

DOI: 10.1109/tsp.2025.3585893
Published: 2025
Container: IEEE transactions on signal processing : a publication of the IEEE Signal Processing Society
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.1109/tsp.2025.3585893,
  title = {An optimal pairwise merge algorithm improves the quality and consistency of nonnegative matrix factorization.},
  author = {Guo Y and Holy TE},
  year = {2025},
  journal = {IEEE transactions on signal processing : a publication of the IEEE Signal Processing Society},
  doi = {10.1109/tsp.2025.3585893},
  url = {https://doi.org/10.1109/tsp.2025.3585893}
}

RIS

TY  - JOUR
TI  - An optimal pairwise merge algorithm improves the quality and consistency of nonnegative matrix factorization.
AU  - Guo Y
AU  - Holy TE
PY  - 2025
JO  - IEEE transactions on signal processing : a publication of the IEEE Signal Processing Society
DO  - 10.1109/tsp.2025.3585893
UR  - https://doi.org/10.1109/tsp.2025.3585893
ER  -

APA

Y, G., & TE, H. (2025). An optimal pairwise merge algorithm improves the quality and consistency of nonnegative matrix factorization.. IEEE transactions on signal processing : a publication of the IEEE Signal Processing Society. https://doi.org/10.1109/tsp.2025.3585893

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pubmed · retrieved 2026-11-10T15:05:17.779Z