Basis sharing and coefficient pruning for efficient neural network compression.
This work proposes a unified compression framework, SaP, that jointly leverages basis sharing and coefficient pruning to reduce redundancies in both convolutional filters and their resulting feature maps and highlights the potential of combining complementary compression strategies to create highly efficient, deployabl...