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CirCNN: Accelerating and Compressing Deep Neural Networks using Block-Circulant Matrices

CirCNN is a neural network architecture that uses block-circulant matrices to reduce the number of parameters and computations.

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Cite this as

Caiwen Ding, Siyu Liao, Yanzhi Wang, Zhe Li, Geng Yuan (2024). Dataset: CirCNN: Accelerating and Compressing Deep Neural Networks using Block-Circulant Matrices. https://doi.org/10.57702/yiqxsvrm

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Additional Info

Field	Value
Created	December 2, 2024
Last update	December 2, 2024
Defined In	https://doi.org/10.48550/arXiv.1811.07755
Author	Caiwen Ding
More Authors	Siyu Liao Yanzhi Wang Zhe Li Geng Yuan