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.LG2020
Compact Learning for Multi-Label Classification
Jiaqi Lv, Tianran Wu, Chenglun Peng +3
Multi-label classification (MLC) studies the problem where each instance is associated with multiple relevant labels, which leads to the exponential growth of output space. MLC enc…