Name
Abstract | ||
|---|---|---|
As a variant of non-negative matrix factorization (NMF), symmetric NMF (SymNMF) can generate the clustering result without additional post-processing, by decomposing a similarity matrix into the product of a clustering indicator matrix and its transpose. However, the similarity matrix in the traditional SymNMF methods is usually predefined, resulting in limited clustering performance. Considering ... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/TCYB.2020.2969684 | IEEE Transactions on Cybernetics |
Keywords | DocType | Volume |
Symmetric matrices,Sparse matrices,Matrix decomposition,Dimensionality reduction,Kernel,Urban areas,Clustering methods | Journal | 51 |
Issue | ISSN | Citations |
5 | 2168-2267 | 4 |
PageRank | References | Authors |
0.38 | 22 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yuheng Jia | 1 | 93 | 13.13 |
| Hui Liu | 2 | 9 | 2.80 |
| Junhui Hou | 3 | 395 | 49.84 |
| Sam Kwong | 4 | 4590 | 315.78 |