28 search results - page 3 / 6 » Constrained Laplacian Eigenmap for dimensionality reduction |
77
Voted
CVPR
2008
IEEE
15 years 11 months ago
2008
IEEE
This paper examines the problem of extracting lowdimensional manifold structure given millions of highdimensional face images. Specifically, we address the computational challenge...
81
Voted
ICONIP
2004
14 years 11 months ago
2004
Algorithms for nonlinear dimensionality reduction (NLDR) find meaningful hidden low-dimensional structures in a high-dimensional space. Current algorithms for NLDR are Isomaps, Loc...
ICML
2010
IEEE
14 years 10 months ago
2010
IEEE
We propose a new dimensionality reduction method, the elastic embedding (EE), that optimises an intuitive, nonlinear objective function of the low-dimensional coordinates of the d...
ICML
2006
IEEE
15 years 10 months ago
2006
IEEE
We present a unified duality view of several recently emerged spectral methods for nonlinear dimensionality reduction, including Isomap, locally linear embedding, Laplacian eigenm...
ICML
2007
IEEE
15 years 10 months ago
2007
IEEE
We study the problem of discovering a manifold that best preserves information relevant to a nonlinear regression. Solving this problem involves extending and uniting two threads ...