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://www.pomyslnaszycie.com/white-and-green-bulletin-board-border-simply-boho-schoolgirl-style-on-sale/