649 citations · 4.6k across the 115 of their papers we have counts for
6 papers · 1 filter
Adversarial Attack on Community Detection by Hiding Individuals
Jia Li, Honglei Zhang, Zhichao Han +3
It has been demonstrated that adversarial graphs, i.e., graphs with imperceptible perturbations added, can cause deep graph models to fail on node/graph classification tasks. In th…
Graph Ordering: Towards the Optimal by Learning
Kangfei Zhao, Yu Rong, Jeffrey Xu Yu +2
Graph representation learning has achieved a remarkable success in many graph-based applications, such as node classification, link prediction, and community detection. These model…
Rumor Detection on Social Media with Bi-Directional Graph Convolutional Networks
Tian Bian, Xi Xiao, Tingyang Xu +4
Social media has been developing rapidly in public due to its nature of spreading new information, which leads to rumors being circulated. Meanwhile, detecting rumors from such mas…
A Restricted Black-box Adversarial Framework Towards Attacking Graph Embedding Models
Heng Chang, Yu Rong, Tingyang Xu +5
With the great success of graph embedding model on both academic and industry area, the robustness of graph embedding against adversarial attack inevitably becomes a central proble…
Unsupervised Adversarial Graph Alignment with Graph Embedding
Chaoqi Chen, Weiping Xie, Tingyang Xu +5
Graph alignment, also known as network alignment, is a fundamental task in social network analysis. Many recent works have relied on partially labeled cross-graph node corresponden…
Cascade-BGNN: Toward Efficient Self-supervised Representation Learning on Large-scale Bipartite Graphs
Chaoyang He, Tian Xie, Yu Rong +4
Bipartite graphs have been used to represent data relationships in many data-mining applications such as in E-commerce recommendation systems. Since learning in graph space is more…