Multi-scale structure-guided graph generation for multi-view semi-supervised classification

Yilin Wu, Zhaoliang Chen, Ying Zou, Shiping Wang, Wenzhong Guo

Abstract: Highlights•Two alternative sampling methods are provided to collect the structural information, and then a statistical technique is employed to generate a fused graph.•An efficient graph generation framework has been developed to construct graphs in multi-view learning.•Comprehensive evaluations of six real-world datasets show the superiority of the proposed framework.