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cs.LG2021
BWCP: Probabilistic Learning-to-Prune Channels for ConvNets via Batch Whitening
Wenqi Shao, Hang Yu, Zhaoyang Zhang +3
This work presents a probabilistic channel pruning method to accelerate Convolutional Neural Networks (CNNs). Previous pruning methods often zero out unimportant channels in traini…
cs.LG2019
Training Robust Deep Neural Networks via Adversarial Noise Propagation
Aishan Liu, Xianglong Liu, Chongzhi Zhang +3
In practice, deep neural networks have been found to be vulnerable to various types of noise, such as adversarial examples and corruption. Various adversarial defense methods have…
cs.LG2019
PDA: Progressive Data Augmentation for General Robustness of Deep Neural Networks
Hang Yu, Aishan Liu, Xianglong Liu +5
Adversarial images are designed to mislead deep neural networks (DNNs), attracting great attention in recent years. Although several defense strategies achieved encouraging robustn…