1 citations · 2 across the 8 of their papers we have counts for
8 papers
Kernel Alignment-based Multi-view Unsupervised Feature Selection with Sample-level Adaptive Graph Learning
Yalan Tan, Yanyong Huang, Zongxin Shen +3
Although multi-view unsupervised feature selection (MUFS) has demonstrated success in dimensionality reduction for unlabeled multi-view data, most existing methods reduce feature r…
Structure-aware Hybrid-order Similarity Learning for Multi-view Unsupervised Feature Selection
Lin Xu, Ke Li, Dongjie Wang +3
Multi-view unsupervised feature selection (MUFS) has recently emerged as an effective dimensionality reduction method for unlabeled multi-view data. However, most existing methods…
Cross-view Joint Learning for Mixed-Missing Multi-view Unsupervised Feature Selection
Zongxin Shen, Yanyong Huang, Dongjie Wang +4
Incomplete multi-view unsupervised feature selection (IMUFS), which aims to identify representative features from unlabeled multi-view data containing missing values, has received…
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…
Enhancing Multi-Robot Semantic Navigation Through Multimodal Chain-of-Thought Score Collaboration
Zhixuan Shen, Haonan Luo, Kexun Chen +2
Understanding how humans cooperatively utilize semantic knowledge to explore unfamiliar environments and decide on navigation directions is critical for house service multi-robot s…
Adaptive Collaborative Correlation Learning-based Semi-Supervised Multi-Label Feature Selection
Li Yang, Yanyong Huang, Dongjie Wang +4
Semi-supervised multi-label feature selection has recently been developed to solve the curse of dimensionality problem in high-dimensional multi-label data with certain samples mis…
Learning Contrastive Feature Representations for Facial Action Unit Detection
Ziqiao Shang, Bin Liu, Fengmao Lv +3
For the Facial Action Unit (AU) detection task, accurately capturing the subtle facial differences between distinct AUs is essential for reliable detection. Additionally, AU detect…
Unified View Imputation and Feature Selection Learning for Incomplete Multi-view Data
Yanyong Huang, Zongxin Shen, Tianrui Li +1
Although multi-view unsupervised feature selection (MUFS) is an effective technology for reducing dimensionality in machine learning, existing methods cannot directly deal with inc…