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cs.LG2024
One for all: A novel Dual-space Co-training baseline for Large-scale Multi-View Clustering
Zisen Kong, Zhiqiang Fu, Dongxia Chang +2
In this paper, we propose a novel multi-view clustering model, named Dual-space Co-training Large-scale Multi-view Clustering (DSCMC). The main objective of our approach is to enha…
cs.LG2021★ 1 cited
Auto-weighted low-rank representation for clustering
Zhiqiang Fu, Yao Zhao, Dongxia Chang +2
In this paper, a novel unsupervised low-rank representation model, i.e., Auto-weighted Low-Rank Representation (ALRR), is proposed to construct a more favorable similarity graph (S…