4 papers
Fast and Robust Contextual Node Representation Learning over Dynamic Graphs
Xingzhi Guo, Silong Wang, Baojian Zhou +2
Real-world graphs grow rapidly with edge and vertex insertions over time, motivating the problem of efficiently maintaining robust node representation over evolving graphs. Recent…
Analyzing the Evolution of Graphs and Texts
Xingzhi Guo
With the recent advance of representation learning algorithms on graphs (e.g., DeepWalk/GraphSage) and natural languages (e.g., Word2Vec/BERT) , the state-of-the art models can eve…
Iterative Methods via Locally Evolving Set Process
Baojian Zhou, Yifan Sun, Reza Babanezhad Harikandeh +3
Given the damping factor and precision tolerance , \citet{andersen2006local} introduced Approximate Personalized PageRank (APPR), the \textit{de facto local method} for appr…
SubAnom: Efficient Subgraph Anomaly Detection Framework over Dynamic Graphs
Chi Zhang, Wenkai Xiang, Xingzhi Guo +2
Given a dynamic graph, the efficient tracking of anomalous subgraphs via their node embeddings poses a significant challenge. Addressing this issue necessitates an effective scorin…