"Sparsity in Deep Learning: Pruning and growth for efficient inference and ..."

Torsten Hoefler et al. (2021)

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type: Journal Article

metadata version: 2024-09-11

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Torsten Hoefler, Dan Alistarh, Tal Ben-Nun, Nikoli Dryden, Alexandra Peste:
Sparsity in Deep Learning: Pruning and growth for efficient inference and training in neural networks. J. Mach. Learn. Res. 22: 241:1-241:124 (2021)

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