543 search results - page 23 / 109 » Nonlinear principal component analysis of noisy data |
ECCV
2000
Springer
14 years 9 months ago
2000
Springer
In recent years several techniques have been proposed for modelling the low-dimensional manifolds, or `subspaces', of natural images. Examples include principal component anal...
ICML
2003
IEEE
14 years 8 months ago
2003
IEEE
In this paper, we address the problem of finding the pre-image of a feature vector in the feature space induced by a kernel. This is of central importance in some kernel applicatio...
NIPS
2004
13 years 9 months ago
2004
In contrast to the equivalence of linear blind source separation and linear independent component analysis it is not possible to recover the original source signal from some unkno...
IDEAL
2004
Springer
14 years 1 months ago
2004
Springer
A common objective in image analysis is dimensionality reduction. The most common often used data-exploratory technique with this objective is principal component analysis. We pro...
MIAR
2006
IEEE
14 years 1 months ago
2006
IEEE
Abstract. A main focus of statistical shape analysis is the description of variability of a population of geometric objects. In this paper, we present work in progress towards mode...