4 citations · 8 across the 8 of their papers we have counts for
9 papers · 1 filter
TRUST-FS: Tensorized Reliable Unsupervised Multi-View Feature Selection for Incomplete Data
Minghui Lu, Yanyong Huang, Minbo Ma +4
Multi-view unsupervised feature selection (MUFS), which selects informative features from multi-view unlabeled data, has attracted increasing research interest in recent years. Alt…
Non-collective Calibrating Strategy for Time Series Forecasting
Bin Wang, Yongqi Han, Minbo Ma +4
Deep learning-based approaches have demonstrated significant advancements in time series forecasting. Despite these ongoing developments, the complex dynamics of time series make i…
CoIFNet: A Unified Framework for Multivariate Time Series Forecasting with Missing Values
Kai Tang, Ji Zhang, Hua Meng +5
Multivariate time series forecasting (MTSF) is a critical task with broad applications in domains such as meteorology, transportation, and economics. Nevertheless, pervasive missin…
Beyond Fixed Variables: Expanding-variate Time Series Forecasting via Flat Scheme and Spatio-temporal Focal Learning
Minbo Ma, Kai Tang, Huan Li +3
Multivariate Time Series Forecasting (MTSF) has long been a key research focus. Traditionally, these studies assume a fixed number of variables, but in real-world applications, Cyb…
Causally-Aware Unsupervised Feature Selection Learning
Zongxin Shen, Yanyong Huang, Dongjie Wang +3
Unsupervised feature selection (UFS) has recently gained attention for its effectiveness in processing unlabeled high-dimensional data. However, existing methods overlook the intri…
UMOD: A Novel and Effective Urban Metro Origin-Destination Flow Prediction Method
Peng Xie, Minbo Ma, Bin Wang +2
Accurate prediction of metro Origin-Destination (OD) flow is essential for the development of intelligent transportation systems and effective urban traffic management. Existing ap…