Name
Abstract | ||
|---|---|---|
•Joint multi-view and ensemble clustering derives a novel clustering scheme SIB.•An extensional MI is formulated for the similarity between features and clusterings.•A novel optimization method is proposed and proven to ensure the convergence of SIB.•The effectiveness of SIB is verified on multiple challenging and practical tasks. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1016/j.inffus.2019.10.006 | Information Fusion |
Keywords | Field | DocType |
Multi-view clustering,Ensemble clustering,Information bottleneck,Mutual information | Data information,Finite set,Pattern recognition,Source data,Artificial intelligence,Mutual information,Information bottleneck method,Partition (number theory),Cluster analysis,Maximization,Mathematics | Journal |
Volume | ISSN | Citations |
56 | 1566-2535 | 3 |
PageRank | References | Authors |
0.39 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xiaoqiang Yan | 1 | 20 | 5.35 |
| Yangdong Ye | 2 | 118 | 29.64 |
| Xueying Qiu | 3 | 5 | 1.08 |
| Hui Yu | 4 | 128 | 21.50 |