98 citations · 172 across the 21 of their papers we have counts for
4 papers · 1 filter
Cross-Layer Strategic Ensemble Defense Against Adversarial Examples
Wenqi Wei, Ling Liu, Margaret Loper +4
Deep neural network (DNN) has demonstrated its success in multiple domains. However, DNN models are inherently vulnerable to adversarial examples, which are generated by adding adv…
Deep Neural Network Ensembles against Deception: Ensemble Diversity, Accuracy and Robustness
Ling Liu, Wenqi Wei, Ka-Ho Chow +4
Ensemble learning is a methodology that integrates multiple DNN learners for improving prediction performance of individual learners. Diversity is greater when the errors of the en…
Denoising and Verification Cross-Layer Ensemble Against Black-box Adversarial Attacks
Ka-Ho Chow, Wenqi Wei, Yanzhao Wu +1
Deep neural networks (DNNs) have demonstrated impressive performance on many challenging machine learning tasks. However, DNNs are vulnerable to adversarial inputs generated by add…
Demystifying Learning Rate Policies for High Accuracy Training of Deep Neural Networks
Yanzhao Wu, Ling Liu, Juhyun Bae +6
Learning Rate (LR) is an important hyper-parameter to tune for effective training of deep neural networks (DNNs). Even for the baseline of a constant learning rate, it is non-trivi…