4 papers · 1 filter
Weight-Informed Self-Explaining Clustering for Mixed-Type Tabular Data
Lehao Li, Qiang Huang, Yihao Ang +3
Clustering mixed-type tabular data is fundamental for exploratory analysis, yet remains challenging due to misaligned numerical-categorical representations, uneven and context-depe…
RFOD: Random Forest-based Outlier Detection for Tabular Data
Yihao Ang, Peicheng Yao, Yifan Bao +4
Outlier detection in tabular data is crucial for safeguarding data integrity in high-stakes domains such as cybersecurity, financial fraud detection, and healthcare, where anomalie…
Towards Controllable Time Series Generation
Yifan Bao, Yihao Ang, Qiang Huang +2
Time Series Generation (TSG) has emerged as a pivotal technique in synthesizing data that accurately mirrors real-world time series, becoming indispensable in numerous applications…
TSGBench: Time Series Generation Benchmark
Yihao Ang, Qiang Huang, Yifan Bao +2
Synthetic Time Series Generation (TSG) is crucial in a range of applications, including data augmentation, anomaly detection, and privacy preservation. Although significant strides…