Quantum-inspired canonical correlation analysis for exponentially large dimensional data.
- DOI
- 10.1016/j.neunet.2020.11.019
- Published
- 2021 Mar
- Container
- Neural networks : the official journal of the International Neural Network Society
- Publisher
- Not recorded
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1016/j.neunet.2020.11.019,
title = {Quantum-inspired canonical correlation analysis for exponentially large dimensional data.},
author = {Koide-Majima N and Majima K},
year = {2021},
journal = {Neural networks : the official journal of the International Neural Network Society},
doi = {10.1016/j.neunet.2020.11.019},
url = {https://doi.org/10.1016/j.neunet.2020.11.019}
}RIS
TY - JOUR TI - Quantum-inspired canonical correlation analysis for exponentially large dimensional data. AU - Koide-Majima N AU - Majima K PY - 2021 JO - Neural networks : the official journal of the International Neural Network Society DO - 10.1016/j.neunet.2020.11.019 UR - https://doi.org/10.1016/j.neunet.2020.11.019 ER -
APA
N, K., & K, M. (2021). Quantum-inspired canonical correlation analysis for exponentially large dimensional data.. Neural networks : the official journal of the International Neural Network Society. https://doi.org/10.1016/j.neunet.2020.11.019
Source records
- pubmed · retrieved 2026-09-25T17:23:20.942Z