36 citations · 59 across the 9 of their papers we have counts for
10 papers
Normality Constraint Learning: Adapting Foundation Models for Time Series Anomaly Detection
Xiaohui Zhou, Yijie Wang, Hongzuo Xu +2
Time Series Foundation Models (TSFMs) achieve strong generalization by learning to reconstruct or forecast broad temporal patterns from large-scale time series during pre-training.…
IMPACT: Influence Modeling for Open-Set Time Series Anomaly Detection
Xiaohui Zhou, Yijie Wang, Hongzuo Xu +3
Open-set anomaly detection (OSAD) is an emerging paradigm designed to utilize limited labeled data from anomaly classes seen in training to identify both seen and unseen anomalies…
Enhancing Kernel Power K-means: Scalable and Robust Clustering with Random Fourier Features and Possibilistic Method
Yixi Chen, Weixuan Liang, Tianrui Liu +4
Kernel power -means (KPKM) leverages a family of means to mitigate local minima issues in kernel -means. However, KPKM faces two key limitations: (1) the computational burden…
Generalization Performance of Ensemble Clustering: From Theory to Algorithm
Xu Zhang, Haoye Qiu, Weixuan Liang +3
Ensemble clustering has demonstrated great success in practice; however, its theoretical foundations remain underexplored. This paper examines the generalization performance of ens…
Mixture of Experts for Node Classification
Yu Shi, Yiqi Wang, WeiXuan Lang +3
Nodes in the real-world graphs exhibit diverse patterns in numerous aspects, such as degree and homophily. However, most existent node predictors fail to capture a wide range of no…
Scalable Incomplete Multi-View Clustering with Structure Alignment
Yi Wen, Siwei Wang, Ke Liang +6
The success of existing multi-view clustering (MVC) relies on the assumption that all views are complete. However, samples are usually partially available due to data corruption or…
Unpaired Multi-View Graph Clustering with Cross-View Structure Matching
Yi Wen, Siwei Wang, Qing Liao +4
Multi-view clustering (MVC), which effectively fuses information from multiple views for better performance, has received increasing attention. Most existing MVC methods assume tha…
Fast Continual Multi-View Clustering with Incomplete Views
Xinhang Wan, Bin Xiao, Xinwang Liu +3
Multi-view clustering (MVC) has gained broad attention owing to its capacity to exploit consistent and complementary information across views. This paper focuses on a challenging i…
Auto-weighted Multi-view Clustering for Large-scale Data
Xinhang Wan, Xinwang Liu, Jiyuan Liu +6
Multi-view clustering has gained broad attention owing to its capacity to exploit complementary information across multiple data views. Although existing methods demonstrate deligh…
Multi-View Spectral Clustering with High-Order Optimal Neighborhood Laplacian Matrix
Weixuan Liang, Sihang Zhou, Jian Xiong +5
Multi-view spectral clustering can effectively reveal the intrinsic cluster structure among data by performing clustering on the learned optimal embedding across views. Though demo…