14 citations · 14 across the 3 of their papers we have counts for
3 papers
cs.CV2022
Boosting Pruned Networks with Linear Over-parameterization
Yu Qian, Jian Cao, Xiaoshuang Li +3
Structured pruning compresses neural networks by reducing channels (filters) for fast inference and low footprint at run-time. To restore accuracy after pruning, fine-tuning is usu…
cs.CV2020
An Once-for-All Budgeted Pruning Framework for ConvNets Considering Input Resolution
Wenyu Sun, Jian Cao, Pengtao Xu +2
We propose an efficient once-for-all budgeted pruning framework (OFARPruning) to find many compact network structures close to winner tickets in the early training stage considerin…
cs.CV2020★ 14 cited
Layer Pruning via Fusible Residual Convolutional Block for Deep Neural Networks
Pengtao Xu, Jian Cao, Fanhua Shang +2
In order to deploy deep convolutional neural networks (CNNs) on resource-limited devices, many model pruning methods for filters and weights have been developed, while only a few t…