13 citations · 28 across the 5 of their papers we have counts for
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cs.LG2021
Fine-Grained AutoAugmentation for Multi-Label Classification
Ya Wang, Hesen Chen, Fangyi Zhang +4
Data augmentation is a commonly used approach to improving the generalization of deep learning models. Recent works show that learned data augmentation policies can achieve better…
cs.LG2020★ 13 cited
WeMix: How to Better Utilize Data Augmentation
Yi Xu, Asaf Noy, Ming Lin +3
Data augmentation is a widely used training trick in deep learning to improve the network generalization ability. Despite many encouraging results, several recent studies did point…
cs.LG2020
Knapsack Pruning with Inner Distillation
Yonathan Aflalo, Asaf Noy, Ming Lin +2
Neural network pruning reduces the computational cost of an over-parameterized network to improve its efficiency. Popular methods vary from -norm sparsification to Neural A…