Joint filter and channel pruning of convolutional neural networks as a bi-level optimization problem-Reference-Cited by-同舟云学术

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Joint filter and channel pruning of convolutional neural networks as a bi-level optimization problem

Published:2024-02-17 Issue:1 Volume:16 Page:71-90
ISSN:1865-9284
Container-title:Memetic Computing
language:en
Short-container-title:Memetic Comp.

Author:

Louati Hassen,Louati Ali,Bechikh Slim,Kariri Elham

Funder

Deanship of Scientific Research, Prince Sattam bin Abdulaziz University

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s12293-024-00406-6.pdf

Reference49 articles.

1. Ankur S, Pekka M, Anton F, Kalyanmoy D (2015) Multi-objective stackelberg game between a regulating authority and a mining company: a case study in environmental economics. Evolut Comput 23(2):217–248

2. Anwar S, Hwang K, Sung W (2017) Structured pruning of deep convolutional neural networks. ACM J Emerg Technol Comput Syst 13(3):1–18

3. Bai X, Wang X, Liu X, Liu Q, Song J, Sebe N, Kim B (2021) Explainable deep learning for efficient and robust pattern recognition: a survey of recent developments. Pattern Recognit 120(1):108102

4. Bhattacharya S, Lane ND (2016) Sparsification and separation of deep learning layers for constrained resource inference on wearables. In: SenSys pp 176–189

5. Chakraborty UK, Janikow CZ (2003) An analysis of gray versus binary encoding in genetic search. Inform Sci 156(3–4):253–269

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