2 citations · 2 across the 4 of their papers we have counts for
4 papers
Achieving Network Resilience through Graph Neural Network-enabled Deep Reinforcement Learning
Xuzeng Li, Tao Zhang, Jian Wang +5
Deep reinforcement learning (DRL) has been widely used in many important tasks of communication networks. In order to improve the perception ability of DRL on the network, some stu…
Generative AI-driven Cross-layer Covert Communication: Fundamentals, Framework and Case Study
Tianhao Liu, Jiqiang Liu, Tao Zhang +5
Ensuring end-to-end cross-layer communication security in military networks by selecting covert schemes between nodes is a key solution for military communication security. With th…
DI-AA: An Interpretable White-box Attack for Fooling Deep Neural Networks
Yixiang Wang, Jiqiang Liu, Xiaolin Chang +2
White-box Adversarial Example (AE) attacks towards Deep Neural Networks (DNNs) have a more powerful destructive capacity than black-box AE attacks in the fields of AE strategies. H…
AppQ: Warm-starting App Recommendation Based on View Graphs
Dan Su, Jiqiang Liu, Sencun Zhu +3
Current app ranking and recommendation systems are mainly based on user-generated information, e.g., number of downloads and ratings. However, new apps often have few (or even no)…