PSE-Net: Channel pruning for Convolutional Neural Networks with parallel-subnets estimator

Shiguang Wang, Tao Xie, Haijun Liu, Xingcheng Zhang, Jian Cheng

Abstract: Highlights•We propose PSE-Net, a novel parallel-subnets estimator for efficient channel pruning.•The prior-distributed-based sampling algorithm to facilitate subnets search.•30%/16% total time for estimator training compared with BCNet/AutoSlim.•Exceeds the SOTAs on ImageNet and downstream tasks for a variety of FLOPs budgets.