2 papers
cs.LG2026
SEHFS: Structural Entropy-Guided High-Order Correlation Learning for Multi-View Multi-Label Feature Selection
Cheng Peng, Yonghao Li, Wanfu Gao +2
In recent years, multi-view multi-label learning (MVML) has attracted extensive attention due to its close alignment to real-world scenarios. Information-theoretic methods have gai…
cs.CV2025
Structure-guided Deep Multi-View Clustering
Jinrong Cui, Xiaohuang Wu, Haitao Zhang +2
Deep multi-view clustering seeks to utilize the abundant information from multiple views to improve clustering performance. However, most of the existing clustering methods often n…