COP prunes CNN filters using correlation-based importance with global normalization and dual regularization on parameter quantity and FLOPs to enable customized compression.
Learning efficient convolutional networks through net- work slimming
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COP: Customized Deep Model Compression via Regularized Correlation-Based Filter-Level Pruning
COP prunes CNN filters using correlation-based importance with global normalization and dual regularization on parameter quantity and FLOPs to enable customized compression.