14 citations · 41 across the 12 of their papers we have counts for
22 papers
Local Contrastive Feature learning for Tabular Data
Zhabiz Gharibshah, Xingquan Zhu
Contrastive self-supervised learning has been successfully used in many domains, such as images, texts, graphs, etc., to learn features without requiring label information. In this…
OPR-Miner: Order-preserving rule mining for time series
Youxi Wu, Xiaoqian Zhao, Yan Li +4
Discovering frequent trends in time series is a critical task in data mining. Recently, order-preserving matching was proposed to find all occurrences of a pattern in a time series…
Deep Forest with Hashing Screening and Window Screening
Pengfei Ma, Youxi Wu, Yan Li +4
As a novel deep learning model, gcForest has been widely used in various applications. However, the current multi-grained scanning of gcForest produces many redundant feature vecto…
OPP-Miner: Order-preserving sequential pattern mining
Youxi Wu, Qian Hu, Yan Li +3
A time series is a collection of measurements in chronological order. Discovering patterns from time series is useful in many domains, such as stock analysis, disease detection, an…
GraSSNet: Graph Soft Sensing Neural Networks
Yu Huang, Chao Zhang, Jaswanth Yella +5
In the era of big data, data-driven based classification has become an essential method in smart manufacturing to guide production and optimize inspection. The industrial data obta…
ST-PCNN: Spatio-Temporal Physics-Coupled Neural Networks for Dynamics Forecasting
Yu Huang, James Li, Min Shi +5
Ocean current, fluid mechanics, and many other spatio-temporal physical dynamical systems are essential components of the universe. One key characteristic of such systems is that c…