2 citations · 2 across the 16 of their papers we have counts for
6 papers · 1 filter
FEAT: A Linear-Complexity Foundation Model for Extremely Large Structured Data
Zhenghang Song, Tang Qian, Lu Chen +7
Structured data is widely used in domains such as healthcare, finance, and scientific data management. Recent studies on structured data foundation models (SFMs) aim to support dat…
TCRL: Temporal-Coupled Adversarial Training for Robust Constrained Reinforcement Learning in Worst-Case Scenarios
Wentao Xu, Zhongming Yao, Weihao Li +4
Constrained Reinforcement Learning (CRL) aims to optimize decision-making policies under constraint conditions, making it highly applicable to safety-critical domains such as auton…
Moon: A Modality Conversion-based Efficient Multivariate Time Series Anomaly Detection
Yuanyuan Yao, Yuhan Shi, Lu Chen +5
Multivariate time series (MTS) anomaly detection identifies abnormal patterns where each timestamp contains multiple variables. Existing MTS anomaly detection methods fall into thr…
MH-GIN: Multi-scale Heterogeneous Graph-based Imputation Network for AIS Data (Extended Version)
Hengyu Liu, Tianyi Li, Yuqiang He +3
Location-tracking data from the Automatic Identification System, much of which is publicly available, plays a key role in a range of maritime safety and monitoring applications. Ho…
Digital Twin-Empowered Voltage Control for Power Systems
Jiachen Xu, Yushuai Li, Torben Bach Pedersen +3
Emerging digital twin technology has the potential to revolutionize voltage control in power systems. However, the state-of-the-art digital twin method suffers from low computation…
UniTE: A Survey and Unified Pipeline for Pre-training Spatiotemporal Trajectory Embeddings
Yan Lin, Zeyu Zhou, Yicheng Liu +8
Spatiotemporal trajectories are sequences of timestamped locations, which enable a variety of analyses that in turn enable important real-world applications. It is common to map tr…