8 citations · 14 across the 5 of their papers we have counts for
5 papers
arXiv4TGC: Large-Scale Datasets for Temporal Graph Clustering
Meng Liu, Ke Liang, Yue Liu +3
Temporal graph clustering (TGC) is a crucial task in temporal graph learning. Its focus is on node clustering on temporal graphs, and it offers greater flexibility for large-scale…
Deep Incomplete Multi-view Clustering with Cross-view Partial Sample and Prototype Alignment
Jiaqi Jin, Siwei Wang, Zhibin Dong +2
The success of existing multi-view clustering relies on the assumption of sample integrity across multiple views. However, in real-world scenarios, samples of multi-view are partia…
Auto-weighted Multi-view Clustering for Large-scale Data
Xinhang Wan, Xinwang Liu, Jiyuan Liu +6
Multi-view clustering has gained broad attention owing to its capacity to exploit complementary information across multiple data views. Although existing methods demonstrate deligh…
Late Fusion Multi-view Clustering via Global and Local Alignment Maximization
Siwei Wang, Xinwang Liu, En Zhu
Multi-view clustering (MVC) optimally integrates complementary information from different views to improve clustering performance. Although demonstrating promising performance in v…
Local Sample-weighted Multiple Kernel Clustering with Consensus Discriminative Graph
Liang Li, Siwei Wang, Xinwang Liu +4
Multiple kernel clustering (MKC) is committed to achieving optimal information fusion from a set of base kernels. Constructing precise and local kernel matrices is proved to be of…