41 citations · 74 across the 4 of their papers we have counts for
5 papers
ZeroGAR: Benchmarking the Adversarial Robustness of Zero-Shot Graph Models
Zhongjian Zhang, Xiao Wang, Busheng Zhang +5
Zero-shot graph models (ZGMs), which learn transferable knowledge from source graphs and directly apply to unseen target graphs without any adaptation, have achieved promising perf…
Rethinking Byzantine Robustness in Federated Recommendation from Sparse Aggregation Perspective
Zhongjian Zhang, Mengmei Zhang, Xiao Wang +4
To preserve user privacy in recommender systems, federated recommendation (FR) based on federated learning (FL) emerges, keeping the personal data on the local client and updating…
Federated Heterogeneous Graph Neural Network for Privacy-preserving Recommendation
Bo Yan, Yang Cao, Haoyu Wang +3
The heterogeneous information network (HIN), which contains rich semantics depicted by meta-paths, has emerged as a potent tool for mitigating data sparsity in recommender systems.…
Abnormal Event Detection via Hypergraph Contrastive Learning
Bo Yan, Cheng Yang, Chuan Shi +2
Abnormal event detection, which refers to mining unusual interactions among involved entities, plays an important role in many real applications. Previous works mostly over-simplif…
Graph Mining for Cybersecurity: A Survey
Bo Yan, Cheng Yang, Chuan Shi +4
The explosive growth of cyber attacks nowadays, such as malware, spam, and intrusions, caused severe consequences on society. Securing cyberspace has become an utmost concern for o…