Towards Optimal Structured CNN Pruning via Generative Adversarial Learning
Towards Optimal Structured CNN Pruning via Generative Adversarial Learning
Structured pruning of filters or neurons has received increased focus for compressing convolutional neural networks. Most existing methods rely on multi-stage optimizations in a layer-wise manner for iteratively pruning and retraining which may not be optimal and may be computation intensive. Besides, these methods are designed for pruning a specific …