Name
Abstract | ||
|---|---|---|
In the past decade, a number of nonlinear dimensionality reduction methods using an affinity graph have been developed for manifold learning. This paper explores a multilevel framework with the goal of reducing the cost of unsupervised manifold learning and preserving the embedding quality at the same time. An application to spectral clustering is also presented. Experimental results indicate that our multilevel approach is an appealing alternative to standard techniques. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1145/1871437.1871493 | CIKM |
Keywords | DocType | Citations |
multilevel framework,manifold learning,appealing alternative,unsupervised manifold,past decade,multilevel manifold,nonlinear dimensionality reduction method,embedding quality,affinity graph,multilevel approach,spectral clustering,nonlinear dimensionality reduction | Conference | 6 |
PageRank | References | Authors |
0.43 | 23 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Haw-ren Fang | 1 | 132 | 13.24 |
| Sophia Sakellaridi | 2 | 15 | 1.07 |
| Yousef Saad | 3 | 1940 | 254.74 |