Abstract:Tensor decomposition has been extensively studied for convolutional neural networks (CNN) model compression. However, the direct decomposition of an uncompressed model into low-rank form causes unavoidable approximation error due to the lack of low-rank property of a pre-trained model. In this manuscript, a CNN model compression method using alternating constraint optimization framework (ACOF) is proposed. Firstly, ACOF formulates tensor decomposition-based model compression as a constraint optimization proble… Show more
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