77 citations · 142 across the 15 of their papers we have counts for
4 papers · 1 filter
Toward Evaluating Robustness of Reinforcement Learning with Adversarial Policy
Xiang Zheng, Xingjun Ma, Shengjie Wang +3
Reinforcement learning agents are susceptible to evasion attacks during deployment. In single-agent environments, these attacks can occur through imperceptible perturbations inject…
FairNeuron: Improving Deep Neural Network Fairness with Adversary Games on Selective Neurons
Xuanqi Gao, Juan Zhai, Shiqing Ma +3
With Deep Neural Network (DNN) being integrated into a growing number of critical systems with far-reaching impacts on society, there are increasing concerns on their ethical perfo…
CARTL: Cooperative Adversarially-Robust Transfer Learning
Dian Chen, Hongxin Hu, Qian Wang +4
Transfer learning eases the burden of training a well-performed model from scratch, especially when training data is scarce and computation power is limited. In deep learning, a ty…
Can We Mitigate Backdoor Attack Using Adversarial Detection Methods?
Kaidi Jin, Tianwei Zhang, Chao Shen +4
Deep Neural Networks are well known to be vulnerable to adversarial attacks and backdoor attacks, where minor modifications on the input are able to mislead the models to give wron…