98 search results - page 2 / 20 » On Point Sampling Versus Space Sampling for Dimensionality R... |
CVPR
2008
IEEE
14 years 7 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...
SIGMOD
2002
ACM
14 years 5 months ago
2002
ACM
With the increased abilities for automated data collection made possible by modern technology, the typical sizes of data collections have continued to grow in recent years. In suc...
IJCAI
2003
13 years 6 months ago
2003
We equate nonlinear dimensionality reduction (NLDR) to graph embedding with side information about the vertices, and derive a solution to either problem in the form of a kernel-ba...
ECCV
2002
Springer
14 years 7 months ago
2002
Springer
Abstract. Principal Component Analysis (PCA) is one of the most popular techniques for dimensionality reduction of multivariate data points with application areas covering many bra...
ICCV
2009
IEEE
14 years 10 months ago
2009
IEEE
We present a manifold learning approach to dimensionality
reduction that explicitly models the manifold as a mapping
from low to high dimensional space. The manifold is
represen...