3 papers
cs.AI2026
FeatureHospital: A Skill-Driven Multi-Agent Framework for Automated Algorithm Customization in Multi-View Multi-Label Feature Selection
Junxuan Li, Zhiqi Chen, Yuzhou Liu +2
Multi-view multi-label feature selection aims to identify a compact and informative feature subset from heterogeneous views while preserving discriminative information for multiple…
cs.AI2025
Combining LLM Semantic Reasoning with GNN Structural Modeling for Multi-View Multi-Label Feature Selection
Zhiqi Chen, Yuzhou Liu, Jiarui Liu +1
Multi-view multi-label feature selection aims to identify informative features from heterogeneous views, where each sample is associated with multiple interdependent labels. This p…
cs.LG2025
Redundancy-optimized Multi-head Attention Networks for Multi-View Multi-Label Feature Selection
Yuzhou Liu, Jiarui Liu, Wanfu Gao
Multi-view multi-label data offers richer perspectives for artificial intelligence, but simultaneously presents significant challenges for feature selection due to the inherent com…