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Suggestion: Cite the following papers #304

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FinAminToastCrunch opened this issue Jul 2, 2024 · 7 comments
Closed

Suggestion: Cite the following papers #304

FinAminToastCrunch opened this issue Jul 2, 2024 · 7 comments

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@FinAminToastCrunch
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FinAminToastCrunch commented Jul 2, 2024

In reference to Ethical Considerations on Pruning, I would suggest citing:

Tran, Cuong, et al. "Pruning has a disparate impact on model accuracy." Advances in neural information processing systems 35 (2022): 17652-17664.

As it discusses how pruning can harm accuracy with respect to inferencing on certain ethnicities.

In reference to Establishing Criteria for Pruning, I believe these two papers would be relevant to cite for the portions on importance scores as they tie together more recent work concerning gradient flow and neuron magnitude:

J. Rachwan, D. Z ̈ugner, B. Charpentier, S. Geisler, M. Ayle, and
S. G ̈unnemann, “Winning the lottery ahead of time: Efficient early
network pruning,” in International Conference on Machine Learning,
ICML 2022, 17-23 July 2022, Baltimore, Maryland, USA (K. Chaudhuri,
S. Jegelka, L. Song, C. Szepesv ́ari, G. Niu, and S. Sabato, eds.),
vol. 162 of Proceedings of Machine Learning Research, pp. 18293–
18309, PMLR, 2022.

E. S. Lubana and R. P. Dick, “A gradient flow framework for analyzing
network pruning,” CoRR, vol. abs/2009.11839, 2020.

@profvjreddi
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@FinAminToastCrunch The link you shared is not working. Could you update the link so I can take at which part you are referring to here.

@profvjreddi
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profvjreddi commented Jul 4, 2024 via email

@profvjreddi
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profvjreddi commented Jul 4, 2024 via email

@FinAminToastCrunch
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Done!

And yes, makes sense.

@profvjreddi
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Dealt with in issue #306 and PR

@profvjreddi
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Thanks @FinAminToastCrunch I finally got a chance to review the changes and make some tweaks an close it.

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