Robust high-order graph learning for incomplete multi-view clustering

Daoyuan Wang, Fujian Ren, Yuntang Zhuang, Cheng Liang

Abstract: Highlights•Our model can handle multi-view data with arbitrary missing scenes.•Our model considers both local and global similarity structures within each view.•We design a low-rank tensor model to explore high-order inter-view correlations.•An iterative optimization strategy is devised to optimize our model.