Rethinking Weight Decay for Efficient Neural Network Pruning
- DOI
- 10.3390/jimaging8030064
- Published
- 2022-03-04
- Container
- Journal of Imaging
- Publisher
- MDPI AG
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.3390/jimaging8030064,
title = {Rethinking Weight Decay for Efficient Neural Network Pruning},
author = {Hugo Tessier and Vincent Gripon and Mathieu Léonardon and Matthieu Arzel and Thomas Hannagan and David Bertrand},
year = {2022},
journal = {Journal of Imaging},
doi = {10.3390/jimaging8030064},
url = {https://doi.org/10.3390/jimaging8030064}
}RIS
TY - JOUR TI - Rethinking Weight Decay for Efficient Neural Network Pruning AU - Hugo Tessier AU - Vincent Gripon AU - Mathieu Léonardon AU - Matthieu Arzel AU - Thomas Hannagan AU - David Bertrand PY - 2022 JO - Journal of Imaging DO - 10.3390/jimaging8030064 UR - https://doi.org/10.3390/jimaging8030064 ER -
APA
Tessier, H., Gripon, V., Léonardon, M., Arzel, M., Hannagan, T., & Bertrand, D. (2022). Rethinking Weight Decay for Efficient Neural Network Pruning. Journal of Imaging. https://doi.org/10.3390/jimaging8030064
Source records
- crossref · retrieved 2026-09-25T17:14:48.821Z