activity
20182020
most citedGraphDefense: Towards Robust Graph Convolutional Networks

22 citations · 22 across the 2 of their papers we have counts for

collaborators

6 papers

cs.LG2020

Energy-based Out-of-distribution Detection

Weitang Liu, Xiaoyun Wang, John D. Owens +1

Determining whether inputs are out-of-distribution (OOD) is an essential building block for safely deploying machine learning models in the open world. However, previous methods re…

cs.LG201922 cited

GraphDefense: Towards Robust Graph Convolutional Networks

Xiaoyun Wang, Xuanqing Liu, Cho-Jui Hsieh

In this paper, we study the robustness of graph convolutional networks (GCNs). Despite the good performance of GCNs on graph semi-supervised learning tasks, previous works have sho…

cs.SI2018

More or Less? Predict the Social Influence of Malicious URLs on Social Media

Chun-Ming Lai, Xiaoyun Wang, Jon W. Chapman +5

Users of Online Social Networks (OSNs) interact with each other more than ever. In the context of a public discussion group, people receive, read, and write comments in response to…

cs.LG2018

Attack Graph Convolutional Networks by Adding Fake Nodes

Xiaoyun Wang, Minhao Cheng, Joe Eaton +2

In this paper, we study the robustness of graph convolutional networks (GCNs). Previous work have shown that GCNs are vulnerable to adversarial perturbation on adjacency or feature…

cs.SI2018

Attacking Strategies and Temporal Analysis Involving Facebook Discussion Groups

Chun-Ming Lai, Xiaoyun Wang, Yunfeng Hong +4

Online social network (OSN) discussion groups are exerting significant effects on political dialogue. In the absence of access control mechanisms, any user can contribute to any OS…

cs.SI2018

Multiple Accounts Detection on Facebook Using Semi-Supervised Learning on Graphs

Xiaoyun Wang, Chun-Ming Lai, Yunfeng Hong +2

In social networks, a single user may create multiple accounts to spread his / her opinions and to influence others, by actively comment on different news pages. It would be benefi…