511 search results - page 11 / 103 » The intrinsic dimensionality of graphs |
ICML
2005
IEEE
14 years 10 months ago
2005
IEEE
Many unsupervised algorithms for nonlinear dimensionality reduction, such as locally linear embedding (LLE) and Laplacian eigenmaps, are derived from the spectral decompositions o...
SDM
2007
SIAM
13 years 11 months ago
2007
SIAM
Dimensionality reduction is among the keys in mining highdimensional data. This paper studies semi-supervised dimensionality reduction. In this setting, besides abundant unlabeled...
MOBIQUITOUS
2007
IEEE
14 years 4 months ago
2007
IEEE
—The skip graph, an application-layer data structure for routing and indexing, may be used in a sensor network to facilitate queries of the distributed k-dimensional data collect...
CCCG
2006
13 years 11 months ago
2006
We study the graph partitioning problem on ddimensional ball graphs in a geometric way. Let B be a set of balls in d-dimensional Euclidean space with radius ratio and -precision....
CVPR
2007
IEEE
14 years 12 months ago
2007
IEEE
Linear Discriminant Analysis (LDA) is a popular statistical approach for dimensionality reduction. LDA captures the global geometric structure of the data by simultaneously maximi...