Demystifying Neural Network Filter Pruning

Understand

Based on filter magnitude ranking (e.g.

• L1 norm), conventional filter pruning methods for Convolutional Neural Networks (CNNs) have been proved with great effectiveness in computation load reduction.
• Although effective, these methods are rarely analyzed in a perspective of filter functionality.
• In this work, we explore the filter pruning and the retraining through qualitative filter functionality interpretation.