Low-rankness and sparsity are often used to guide the compression of convolutional neural networks (CNNs) separately. Since they capture global and local structure of a matrix respectively. we combine these two complementary properties together to pursue better network compression performance. Most existing low-rank or sparse compression methods compress the networks by approximating ... https://lockdownsecuritycanada.shop/product-category/key-fob-shell/
Compressing by Learning in a Low-Rank and Sparse Decomposition Form
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