166 search results - page 3 / 34 » Learning a kernel matrix for nonlinear dimensionality reduct... |
ICML
2007
IEEE
14 years 5 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 ...
CVPR
2008
IEEE
14 years 6 months ago
2008
IEEE
Linear Discriminant Analysis (LDA), which works by maximizing the within-class similarity and minimizing the between-class similarity simultaneously, is a popular dimensionality r...
CVPR
2008
IEEE
14 years 6 months ago
2008
IEEE
We propose a novel algorithm for clustering data sampled from multiple submanifolds of a Riemannian manifold. First, we learn a representation of the data using generalizations of...
NIPS
2008
13 years 6 months ago
2008
Recently, supervised dimensionality reduction has been gaining attention, owing to the realization that data labels are often available and indicate important underlying structure...
ESANN
2008
13 years 6 months ago
2008
Abstract. Nonlinear dimensionality reduction aims at providing lowdimensional representions of high-dimensional data sets. Many new methods have been proposed in the recent years, ...