Two-step affinity matrix learning for multi-view subspace clustering

Tao Zhang, Yunhao Yuan, Xiaobo Shen, Fan Liu

Abstract: Highlights•Two-step affinity matrix learning is proposed for multi-view clustering.•The subspace and graph models are combined to capture the data structure.•The unified good neighbors learning is used to reflect the sample correlation.•The efficient algorithms and theoretical analyses are provided for our model.