Nonlinear Power Method for Computing Eigenvectors of Proximal Operators and Neural Networks

Leon Bungert, Ester Hait-Fraenkel, Nicolas Papadakis, Guy Gilboa

DOI: 10.1137/20m1384154
Published: 2021
Container: SIAM Journal on Imaging Sciences
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.1137/20m1384154,
  title = {Nonlinear Power Method for Computing Eigenvectors of Proximal Operators and Neural Networks},
  author = {Leon Bungert and Ester Hait-Fraenkel and Nicolas Papadakis and Guy Gilboa},
  year = {2021},
  journal = {SIAM Journal on Imaging Sciences},
  doi = {10.1137/20m1384154},
  url = {https://doi.org/10.1137/20m1384154}
}

RIS

TY  - JOUR
TI  - Nonlinear Power Method for Computing Eigenvectors of Proximal Operators and Neural Networks
AU  - Leon Bungert
AU  - Ester Hait-Fraenkel
AU  - Nicolas Papadakis
AU  - Guy Gilboa
PY  - 2021
JO  - SIAM Journal on Imaging Sciences
DO  - 10.1137/20m1384154
UR  - https://doi.org/10.1137/20m1384154
ER  -

APA

Bungert, L., Hait-Fraenkel, E., Papadakis, N., & Gilboa, G. (2021). Nonlinear Power Method for Computing Eigenvectors of Proximal Operators and Neural Networks. SIAM Journal on Imaging Sciences. https://doi.org/10.1137/20m1384154

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hal · retrieved 2026-11-10T07:50:31.028Z