Multivariate time series anomaly detection is crucial for failure diagnosis, network security, and intelligent operations. Reconstruction-based approaches are well suited for unsupervised scenarios, as they detect anomalies without labeled data and model complex temporal patterns through reconstruction. However, despit...
Xiao-Wei Jia, Sheng-Xi Wang, Kai-Kai Yang et al.· Proceedings of the 35th ACM...· 0 citations
By bridging the representation and prediction spaces, MOLN effectively addresses the label-co-occurrence problem, achieving state-of-the-art performance on benchmark datasets with significant improvements.
Yan Chen, Zong-Han Li, Liang-Jing Liu et al.· Mathematics· 0 citations
Multi-view Clustering via Manifold Decomposition is proposed, which directly infers cluster labels from multi-view data without explicit similarity graph construction or anchor selection, and reformulates multi-view clustering as a unified multi-view regression problem, where cluster labels are optimized as model varia...
Xiao-Wei Zhao, Xin-Yue Kou, Yan Chen et al.· Proceedings of the Thirty-Fi...· 0 citations
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