Pruning becomes increasingly popular as we seek to migrate deep learning to smaller mobile platforms. The paper demonstrates a pruning technique that not only outperforms baseline models, but also proves a high compression ratio is achievable with negligible loss of accuracy. It is able to achieve such results by introducing a novel hierarchical selection mechanism as the basis of pruning.

• Neural Network Compression
• Topdown selection
• Pruning mechanisms