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A multi-agent reinforce- ment learning based approach for automatic filter pruning,

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Correction Crossref 1 open · 1 total · 0 disputed
DOI
10.1038/s41598-024-82562-w
Notice DOI
10.1038/s41598-025-98325-0
Event date
2025-04-23
Machine twin
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01One-hop citing occurrences

Correction Open
Dynamic Sensitivity Filter Pruning using Multi-Agent Reinforcement Learning For DCNN's

ref [13] · 2509.05446 · notice #8473 · dispute

Raw extraction · citation context

Li, and J. Zhao, "An efficient multi-agent reinforce- ment learning framework for neural network compression," Neurocom- puting, vol. 428, pp. 132-144, 2021. [13] Z. Li, X. Zuo, Y . Song, D. Liang, and Z. Xie, "A multi-agent reinforce- ment learning based approach for automatic filter pruning," Sci. Rep., vol. 14, no. 1, p. 31193, Dec. 2024, doi: 10.1038/s41598-024-82562-w. [14] E. Camci, M. Gupta, M. Wu, and J. Lin, "QLP: Deep Q-learning for pruning deep neural networks," IEEE Trans. Circuits Syst. Video Technol., vol. 32, no. 10, pp. 6488-6501, 2022. [15] G. Hinton, O. Vinyals, and J. Dean, "Distilling the knowledge in a neural network," Comput. Sci., vol. 14, no. 7, pp. 38-39, 2015. [16] Z. Liu, J. Li, Z. Shen, G.

Parser render (TeX stripped for reading; raw above is the evidence)

Li, and J. Zhao, "An efficient multi-agent reinforce- ment learning framework for neural network compression," Neurocom- puting, vol. 428, pp. 132-144, 2021. [13] Z. Li, X. Zuo, Y . Song, D. Liang, and Z. Xie, "A multi-agent reinforce- ment learning based approach for automatic filter pruning," Sci. Rep., vol. 14, no. 1, p. 31193, Dec. 2024, doi: 10.1038/s41598-024-82562-w. [14] E. Camci, M. Gupta, M. Wu, and J. Lin, "QLP: Deep Q-learning for pruning deep neural networks," IEEE Trans. Circuits Syst. Video Technol., vol. 32, no. 10, pp. 6488-6501, 2022. [15] G. Hinton, O. Vinyals, and J. Dean, "Distilling the knowledge in a neural network," Comput. Sci., vol. 14, no. 7, pp. 38-39, 2015. [16] Z. Liu, J. Li, Z. Shen, G

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