no code implementations • 23 Jan 2024 • Hao Yang, Hua Mao, Wai Lok Woo, Jie Chen, Xi Peng
Furthermore, the representation process for clustering is enhanced through spectral clustering, and the consistency across multiple views is improved.
no code implementations • 20 Nov 2023 • Jie Chen, Zhiming Li, Hua Mao, Wai Lok Woo, Xi Peng
In this paper, we propose a cross-view graph consistency learning (CGCL) method that learns invariant graph representations for link prediction.
1 code implementation • ICCV 2023 • Jie Chen, Hua Mao, Wai Lok Woo, Xi Peng
Then, a cluster-level CVCL strategy is presented to explore consistent semantic label information among the multiple views in the fine-tuning stage.
no code implementations • 31 Oct 2014 • Jie Chen, Haixian Zhang, Hua Mao, Yongsheng Sang, Zhang Yi
We propose a symmetric low-rank representation (SLRR) method for subspace clustering, which assumes that a data set is approximately drawn from the union of multiple subspaces.
no code implementations • 7 Mar 2014 • Jie Chen, Hua Mao, Yongsheng Sang, Zhang Yi
In this paper, we propose a low-rank representation with symmetric constraint (LRRSC) method for robust subspace clustering.