Area of research
Computational Theory and Mathematics · Artificial Intelligence
Research interest
Research focused on Feature selection and Rough set, with related work in Artificial intelligence, Granularity, Granular computing. Notable publications include 'Label distribution learning: A local collaborative mechanism', 'Robust supervised rough granular description model with the principle of justifiable granularity', and 'Triple-G: a new MGRS and attribute reduction'.
Distributed multi-label feature selection via feature-label information granulation
Class-specific semi-supervised feature selection with fuzzy convex balling information granularity
Margin-Aware Fuzzy Rough Feature Selection: Bridging Uncertainty Characterization and Pattern Classification
Dual-Channel Fuzzy Interaction Information Fused Feature Selection With Fuzzy Sparse and Shared Granularities
Multi-label learning with Relief-based label-specific feature selection
A Q-learning approach to attribute reduction
Robust supervised rough granular description model with the principle of justifiable granularity
Triple-G: a new MGRS and attribute reduction
Label distribution learning: A local collaborative mechanism