Dataset Groups Activity Stream 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. BibTex: @dataset{Caiwen_Ding_and_Siyu_Liao_and_Yanzhi_Wang_and_Zhe_Li_and_Geng_Yuan_2024, abstract = {CirCNN is a neural network architecture that uses block-circulant matrices to reduce the number of parameters and computations.}, author = {Caiwen Ding and Siyu Liao and Yanzhi Wang and Zhe Li and Geng Yuan}, doi = {10.57702/yiqxsvrm}, institution = {No Organization}, keyword = {'Block-Circulant Matrices', 'CirCNN', 'Deep Neural Networks'}, month = {dec}, publisher = {TIB}, title = {CirCNN: Accelerating and Compressing Deep Neural Networks using Block-Circulant Matrices}, url = {https://service.tib.eu/ldmservice/dataset/circnn--accelerating-and-compressing-deep-neural-networks-using-block-circulant-matrices}, year = {2024} }
