Feb. 19, 2024, 5:43 a.m. | Andrey Kuzmin, Markus Nagel, Mart van Baalen, Arash Behboodi, Tijmen Blankevoort

cs.LG updates on arXiv.org arxiv.org

arXiv:2307.02973v2 Announce Type: replace
Abstract: Neural network pruning and quantization techniques are almost as old as neural networks themselves. However, to date only ad-hoc comparisons between the two have been published. In this paper, we set out to answer the question on which is better: neural network quantization or pruning? By answering this question, we hope to inform design decisions made on neural network hardware going forward. We provide an extensive comparison between the two techniques for compressing deep neural …

abstract arxiv cs.lg network networks neural network neural networks paper pruning quantization quantization techniques question set type

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