63 search results - page 1 / 13 » Sample-dependent graph construction with application to dime... |
IJON
2010
13 years 2 months ago
2010
Graph construction plays a key role on learning algorithms based on graph Laplacian. However, the traditional graph construction approaches of -neighborhood and k-nearest-neighbor...
ICMLA
2008
13 years 6 months ago
2008
Dimension reduction techniques have been successfully applied to face recognition and text information retrieval. The process can be time-consuming when the data set is large. Thi...
NIPS
2004
13 years 6 months ago
2004
Many machine learning algorithms for clustering or dimensionality reduction take as input a cloud of points in Euclidean space, and construct a graph with the input data points as...
NIPS
2001
13 years 6 months ago
2001
Drawing on the correspondence between the graph Laplacian, the Laplace-Beltrami operator on a manifold, and the connections to the heat equation, we propose a geometrically motiva...
PAMI
2006
13 years 4 months ago
2006
We provide evidence that non-linear dimensionality reduction, clustering and data set parameterization can be solved within one and the same framework. The main idea is to define ...