Name
Abstract | ||
|---|---|---|
Graph-based dimensionality reduction techniques have been widely and successfully applied to clustering and classification tasks. The basis of these algorithms is the constructed graph which dictates their performance. In general, the graph is defined by the input affinity matrix. However, the affinity matrix derived from the data is sometimes suboptimal for dimension reduction as the data used ar... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/TIP.2018.2810515 | IEEE Transactions on Image Processing |
Keywords | Field | DocType |
Manifolds,Dimensionality reduction,Principal component analysis,Clustering algorithms,Task analysis,Dictionaries | Residual,Dimensionality reduction,Embedding,Pattern recognition,Projection (linear algebra),Theoretical computer science,Artificial intelligence,Nonlinear dimensionality reduction,Cluster analysis,Mathematics,Manifold,Principal component analysis | Journal |
Volume | Issue | ISSN |
27 | 6 | 1057-7149 |
Citations | PageRank | References |
8 | 0.46 | 12 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Wei Wang | 1 | 131 | 14.16 |
| Yan Yan | 2 | 691 | 31.13 |
| Feiping Nie | 3 | 7061 | 309.42 |
| Shuicheng Yan | 4 | 162 | 10.26 |
| Nicu Sebe | 5 | 7013 | 403.03 |