3 citations · 3 across the 2 of their papers we have counts for
2 papers
cs.LG2023
Getting Away with More Network Pruning: From Sparsity to Geometry and Linear Regions
Junyang Cai, Khai-Nguyen Nguyen, Nishant Shrestha +5
One surprising trait of neural networks is the extent to which their connections can be pruned with little to no effect on accuracy. But when we cross a critical level of parameter…
cs.LG2022★ 3 cited
Recall Distortion in Neural Network Pruning and the Undecayed Pruning Algorithm
Aidan Good, Jiaqi Lin, Hannah Sieg +5
Pruning techniques have been successfully used in neural networks to trade accuracy for sparsity. However, the impact of network pruning is not uniform: prior work has shown that t…