39 citations · 41 across the 11 of their papers we have counts for
5 papers · 1 filter
SPEED: Streaming Partition and Parallel Acceleration for Temporal Interaction Graph Embedding
Xi Chen, Yongxiang Liao, Yun Xiong +4
Temporal Interaction Graphs (TIGs) are widely employed to model intricate real-world systems such as financial systems and social networks. To capture the dynamism and interdepende…
RDGSL: Dynamic Graph Representation Learning with Structure Learning
Siwei Zhang, Yun Xiong, Yao Zhang +4
Temporal Graph Networks (TGNs) have shown remarkable performance in learning representation for continuous-time dynamic graphs. However, real-world dynamic graphs typically contain…
iLoRE: Dynamic Graph Representation with Instant Long-term Modeling and Re-occurrence Preservation
Siwei Zhang, Yun Xiong, Yao Zhang +3
Continuous-time dynamic graph modeling is a crucial task for many real-world applications, such as financial risk management and fraud detection. Though existing dynamic graph mode…
Flexible Differentially Private Vertical Federated Learning with Adaptive Feature Embeddings
Yuxi Mi, Hongquan Liu, Yewei Xia +3
The emergence of vertical federated learning (VFL) has stimulated concerns about the imperfection in privacy protection, as shared feature embeddings may reveal sensitive informati…
TIGER: Temporal Interaction Graph Embedding with Restarts
Yao Zhang, Yun Xiong, Yongxiang Liao +4
Temporal interaction graphs (TIGs), consisting of sequences of timestamped interaction events, are prevalent in fields like e-commerce and social networks. To better learn dynamic…