Name
Abstract | ||
|---|---|---|
Recently, multi-view clustering methods based on high-order sample affinities to ease learning complex structures attract much attention. However, most of the methods used pre-defined similarity, which is easy to be corrupted by noises and yield suboptimal performance. To tackle with this issue, this paper proposes a novel multi-view clustering method, named by WHSF, which seeks to learn a self-we... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/ICME51207.2021.9428090 | 2021 IEEE International Conference on Multimedia and Expo (ICME) |
Keywords | DocType | ISBN |
Measurement,Clustering methods,Conferences,Clustering algorithms,Benchmark testing,Robustness,Mutual information | Conference | 978-1-6654-3864-3 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hong Peng | 1 | 14 | 10.33 |
| Hongmin Cai | 2 | 3 | 4.90 |