Name
Abstract | ||
|---|---|---|
A general nonparametric technique is proposed for the description of geometric manifold energy of unorganized data. Minimizing the energy leads to an optimal cycle, from which underlying manifolds are easily distinguished. We design a new framework for manifold clustering based on energy minimization. In addition, we propose the active tabu search method to approximately solve for the optimal solution to energy minimization. We have applied the proposed technique to both synthetic and real data. Experimental results show that the method is feasible and promising in manifold clustering. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1007/978-3-642-01510-6_76 | ISNN (2) |
Keywords | Field | DocType |
manifold clustering,optimal solution,underlying manifold,energy minimization,general nonparametric technique,active tabu search method,proposed technique,optimal cycle,geometric manifold energy,tabu search | Mathematical optimization,Computer science,Manifold alignment,Nonparametric statistics,Artificial intelligence,Discrete curvature,Cluster analysis,Tabu search,Manifold,Machine learning,Energy minimization | Conference |
Volume | ISSN | Citations |
5552 | 0302-9743 | 0 |
PageRank | References | Authors |
0.34 | 4 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hongyu Li | 1 | 443 | 32.34 |
| Qiyong Guo | 2 | 22 | 5.31 |
| Jinyuan Jia | 3 | 149 | 32.76 |
| Jussi Parkkinen | 4 | 289 | 50.06 |