Triplets-based large-scale multi-view spectral clustering

Tianchuan Yang, Chang-Dong Wang, Jipeng Guo, Xiangcheng Li, Man-Sheng Chen, Shuping Dang, Haiqiang Chen

Abstract: Highlights•A fast multi-view clustering based on higher-order triplet relation is proposed.•Triplet enhancement strategy is designed to improve positive and negative examples.•Neighborhood-based similarity and triplet learning preserve local data structure.•Utilizing triplets to guide the learning of high-quality low-dimensional embedding.•A fast sparse spectral clustering method is designed for the sparse graph.