14 citations · 51 across the 12 of their papers we have counts for
4 papers · 1 filter
DecAug: Out-of-Distribution Generalization via Decomposed Feature Representation and Semantic Augmentation
Haoyue Bai, Rui Sun, Lanqing Hong +5
While deep learning demonstrates its strong ability to handle independent and identically distributed (IID) data, it often suffers from out-of-distribution (OoD) generalization, wh…
Batch Group Normalization
Xiao-Yun Zhou, Jiacheng Sun, Nanyang Ye +6
Deep Convolutional Neural Networks (DCNNs) are hard and time-consuming to train. Normalization is one of the effective solutions. Among previous normalization methods, Batch Normal…
Amata: An Annealing Mechanism for Adversarial Training Acceleration
Nanyang Ye, Qianxiao Li, Xiao-Yun Zhou +1
Despite the empirical success in various domains, it has been revealed that deep neural networks are vulnerable to maliciously perturbed input data that much degrade their performa…
Achieving Adversarial Robustness via Sparsity
Shufan Wang, Ningyi Liao, Liyao Xiang +2
Network pruning has been known to produce compact models without much accuracy degradation. However, how the pruning process affects a network's robustness and the working mechanis…