2021
Network Pruning That Matters: A Case Study on Retraining Variants
ICLR 2021poster
Network pruning is an effective method to reduce the computational expense of over-parameterized neural networks for deployment on low-resource systems. Recent state-of-the-art techniques for retraining pruned networks such as weight rewinding and learning rate rewinding have been shown to outperfor…