PCAS: Pruning Channels with Attention Statistics for Deep Network Compression
Abstract
Compression techniques for deep neural networks are important for implementing them on small embedded devices. In particular, channel-pruning is a useful technique for realizing compact networks. However, many conventional methods require manual setting of compression ratios in each layer. It is difficult to analyze the relationships between all layers, especially for deeper models. To address these issues, we propose a simple channel-pruning...
Paper Details
Title
PCAS: Pruning Channels with Attention Statistics for Deep Network Compression
Published Date
Jun 14, 2018
Journal
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