591 citations · 776 across the 8 of their papers we have counts for
8 papers
Differentially Private Data Generative Models
Qingrong Chen, Chong Xiang, Minhui Xue +4
Deep neural networks (DNNs) have recently been widely adopted in various applications, and such success is largely due to a combination of algorithmic breakthroughs, computation re…
Secure Deep Learning Engineering: A Software Quality Assurance Perspective
Lei Ma, Felix Juefei-Xu, Minhui Xue +7
Over the past decades, deep learning (DL) systems have achieved tremendous success and gained great popularity in various applications, such as intelligent machines, image processi…
Reinforcement Learning with Perturbed Rewards
Jingkang Wang, Yang Liu, Bo Li
Recent studies have shown that reinforcement learning (RL) models are vulnerable in various noisy scenarios. For instance, the observed reward channel is often subject to noise in…
DeepHunter: Hunting Deep Neural Network Defects via Coverage-Guided Fuzzing
Xiaofei Xie, Lei Ma, Felix Juefei-Xu +7
In company with the data explosion over the past decade, deep neural network (DNN) based software has experienced unprecedented leap and is becoming the key driving force of many n…
Combinatorial Testing for Deep Learning Systems
Lei Ma, Fuyuan Zhang, Minhui Xue +4
Deep learning (DL) has achieved remarkable progress over the past decade and been widely applied to many safety-critical applications. However, the robustness of DL systems recentl…
DeepMutation: Mutation Testing of Deep Learning Systems
Lei Ma, Fuyuan Zhang, Jiyuan Sun +8
Deep learning (DL) defines a new data-driven programming paradigm where the internal system logic is largely shaped by the training data. The standard way of evaluating DL models i…