91 search results - page 9 / 19 » Non-linear Dimensionality Reduction by Locally Linear Isomap... |
TIT
2008
13 years 7 months ago
2008
Distributed estimation of an unknown signal is a common task in sensor networks. The scenario usually envisioned consists of several nodes, each making an observation correlated wi...
FGR
2006
IEEE
14 years 1 months ago
2006
IEEE
An unsupervised nonparametric approach is proposed to automatically extract representative face samples (exemplars) from a video sequence or an image set for multipleshot face rec...
ICML
2005
IEEE
14 years 8 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...
PR
2006
13 years 7 months ago
2006
In the past few years, some nonlinear dimensionality reduction (NLDR) or nonlinear manifold learning methods have aroused a great deal of interest in the machine learning communit...
ICPR
2006
IEEE
14 years 8 months ago
2006
IEEE
1 A kernel determines the inductive bias of a learning algorithm on a specific data set, and it is beneficial to design specific kernel for a given data set. In this work, we propo...