24 citations · 39 across the 6 of their papers we have counts for
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cs.LG2024★ 4 cited
PeFAD: A Parameter-Efficient Federated Framework for Time Series Anomaly Detection
Ronghui Xu, Hao Miao, Senzhang Wang +2
With the proliferation of mobile sensing techniques, huge amounts of time series data are generated and accumulated in various domains, fueling plenty of real-world applications. I…
cs.LG2024★ 24 cited
A Survey of Graph Neural Networks in Real world: Imbalance, Noise, Privacy and OOD Challenges
Wei Ju, Siyu Yi, Yifan Wang +10
Graph-structured data exhibits universality and widespread applicability across diverse domains, such as social network analysis, biochemistry, financial fraud detection, and netwo…
cs.LG2022
Interpretable and Effective Reinforcement Learning for Attacking against Graph-based Rumor Detection
Yuefei Lyu, Xiaoyu Yang, Jiaxin Liu +3
Social networks are frequently polluted by rumors, which can be detected by advanced models such as graph neural networks. However, the models are vulnerable to attacks and underst…