134 search results - page 2 / 27 » Random Projections for Manifold Learning |
ICML
2007
IEEE
14 years 7 months ago
2007
IEEE
In this work we take a novel view of nonlinear manifold learning. Usually, manifold learning is formulated in terms of finding an embedding or `unrolling' of a manifold into ...
ICASSP
2010
IEEE
13 years 6 months ago
2010
IEEE
The characterization of signals and images in manifolds often lead to efficient dimensionality reduction algorithms based on manifold distance computation for analysis or classi...
TSP
2010
13 years 1 months ago
2010
Nonparametric Bayesian methods are employed to constitute a mixture of low-rank Gaussians, for data x RN that are of high dimension N but are constrained to reside in a low-dimen...
ICIP
2008
IEEE
14 years 8 months ago
2008
IEEE
In this paper, we focus on the use of random projections as a dimensionality reduction tool for sampled manifolds in highdimensional Euclidean spaces. We show that geodesic paths ...
GRC
2008
IEEE
13 years 7 months ago
2008
IEEE
Manifold learning can discover the structure of high dimensional data and provides understanding of multidimensional patterns by preserving the local geometric characteristics. Ho...