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cs.LG2025
TSGDiff: Rethinking Synthetic Time Series Generation from a Pure Graph Perspective
Lifeng Shen, Xuyang Li, Lele Long
Diffusion models have shown great promise in data generation, yet generating time series data remains challenging due to the need to capture complex temporal dependencies and struc…
cs.LG2025
Finding Time Series Anomalies using Granular-ball Vector Data Description
Lifeng Shen, Liang Peng, Ruiwen Liu +2
Modeling normal behavior in dynamic, nonlinear time series data is challenging for effective anomaly detection. Traditional methods, such as nearest neighbor and clustering approac…
cs.LG2025
Granular-Ball-Induced Multiple Kernel K-Means
Shuyin Xia, Yifan Wang, Lifeng Shen +1
Most existing multi-kernel clustering algorithms, such as multi-kernel K-means, often struggle with computational efficiency and robustness when faced with complex data distributio…