123 search results - page 6 / 25 » Nonrigid Embeddings for Dimensionality Reduction |
ICPR
2008
IEEE
14 years 9 months ago
2008
IEEE
In this paper, we propose a new nonlinear dimensionality reduction algorithm by adopting regularized least-square criterion on local areas of the data distribution. We first propo...
NIPS
2004
13 years 9 months ago
2004
We describe a way of using multiple different types of similarity relationship to learn a low-dimensional embedding of a dataset. Our method chooses different, possibly overlappin...
COMPGEOM
2007
ACM
13 years 11 months ago
2007
ACM
In this paper we show that dimensionality reduction (i.e., Johnson-Lindenstrauss lemma) preserves not only the distances between static points, but also between moving points, and...
ICML
2006
IEEE
14 years 8 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...
ICONIP
2004
13 years 9 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...