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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.

Data and Resources

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

DOI retrieved: December 2, 2024

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