31 citations · 69 across the 11 of their papers we have counts for
6 papers · 1 filter
MetaSTH-Sleep: Towards Effective Few-Shot Sleep Stage Classification for Health Management with Spatial-Temporal Hypergraph Enhanced Meta-Learning
Jingyu Li, Tiehua Zhang, Jinze Wang +6
Accurate classification of sleep stages based on bio-signals is fundamental not only for automatic sleep stage annotation, but also for clinical health management and continuous sl…
HyperSMOTE: A Hypergraph-based Oversampling Approach for Imbalanced Node Classifications
Ziming Zhao, Tiehua Zhang, Zijian Yi +1
Hypergraphs are increasingly utilized in both unimodal and multimodal data scenarios due to their superior ability to model and extract higher-order relationships among nodes, comp…
CHASE: A Causal Hypergraph based Framework for Root Cause Analysis in Multimodal Microservice Systems
Ziming Zhao, Zhenwei Wang, Tiehua Zhang +7
In recent years, the widespread adoption of distributed microservice architectures within the industry has significantly increased the demand for enhanced system availability and r…
Exploiting Spatial-temporal Data for Sleep Stage Classification via Hypergraph Learning
Yuze Liu, Ziming Zhao, Tiehua Zhang +5
Sleep stage classification is crucial for detecting patients' health conditions. Existing models, which mainly use Convolutional Neural Networks (CNN) for modelling Euclidean data…
Learning from Heterogeneity: A Dynamic Learning Framework for Hypergraphs
Tiehua Zhang, Yuze Liu, Zhishu Shen +4
Graph neural network (GNN) has gained increasing popularity in recent years owing to its capability and flexibility in modeling complex graph structure data. Among all graph learni…
An Adaptive Federated Relevance Framework for Spatial Temporal Graph Learning
Tiehua Zhang, Yuze Liu, Zhishu Shen +4
Spatial-temporal data contains rich information and has been widely studied in recent years due to the rapid development of relevant applications in many fields. For instance, medi…