148 search results - page 8 / 30 » Riemannian Manifold Learning for Nonlinear Dimensionality Re... |
NIPS
2003
13 years 8 months ago
2003
We introduce an information theoretic method for nonparametric, nonlinear dimensionality reduction, based on the infinite cluster limit of rate distortion theory. By constraining...
ICPR
2006
IEEE
14 years 8 months ago
2006
IEEE
We present a dynamic inference algorithm in a globally parameterized nonlinear manifold and demonstrate it on the problem of visual tracking. An appearance manifold is usually non...
ESANN
2007
13 years 9 months ago
2007
Local algorithms for non-linear dimensionality reduction [1], [2], [3], [4], [5] and semi-supervised learning algorithms [6], [7] use spectral decomposition based on a nearest neig...
NIPS
1997
13 years 8 months ago
1997
Nonlinear dimensionality reduction is formulated here as the problem of trying to find a Euclidean feature-space embedding of a set of observations that preserves as closely as p...
ICPR
2002
IEEE
14 years 8 months ago
2002
IEEE
This paper considers a recently proposed method for unsupervised learning and dimensionality reduction, locally linear embedding (LLE). LLE computes a compact representation of hi...