NNR-GL: A Measure to Detect Co-Nonlinearity Based on Neural Network Regression Regularized by Group Lasso
- DOI
- 10.1109/access.2021.3111105
- Published
- 2021
- Container
- IEEE Access
- Publisher
- Institute of Electrical and Electronics Engineers (IEEE)
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1109/access.2021.3111105,
title = {NNR-GL: A Measure to Detect Co-Nonlinearity Based on Neural Network Regression Regularized by Group Lasso},
author = {Miho Ohsaki and Naoya Kishimoto and Hayato Sasaki and Ryoji Ikeura and Shigeru Katagiri and Kei Ohnishi and Yakub Sebastian and Patrick Then},
year = {2021},
journal = {IEEE Access},
doi = {10.1109/access.2021.3111105},
url = {https://doi.org/10.1109/access.2021.3111105}
}RIS
TY - JOUR TI - NNR-GL: A Measure to Detect Co-Nonlinearity Based on Neural Network Regression Regularized by Group Lasso AU - Miho Ohsaki AU - Naoya Kishimoto AU - Hayato Sasaki AU - Ryoji Ikeura AU - Shigeru Katagiri AU - Kei Ohnishi AU - Yakub Sebastian AU - Patrick Then PY - 2021 JO - IEEE Access DO - 10.1109/access.2021.3111105 UR - https://doi.org/10.1109/access.2021.3111105 ER -
APA
Ohsaki, M., Kishimoto, N., Sasaki, H., Ikeura, R., Katagiri, S., Ohnishi, K., Sebastian, Y., & Then, P. (2021). NNR-GL: A Measure to Detect Co-Nonlinearity Based on Neural Network Regression Regularized by Group Lasso. IEEE Access. https://doi.org/10.1109/access.2021.3111105
Source records
- crossref · retrieved 2026-09-26T04:41:31.026Z