Investigating Channel Pruning through Structural Redundancy Reduction -- A Statistical Study

16 May 2019Chengcheng LiZi WangDali WangXiangyang WangHairong Qi

Most existing channel pruning methods formulate the pruning task from a perspective of inefficiency reduction which iteratively rank and remove the least important filters, or find the set of filters that minimizes some reconstruction errors after pruning. In this work, we investigate the channel pruning from a new perspective with statistical modeling... (read more)

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