49 search results - page 2 / 10 » Dimensionality Reduction by Learning an Invariant Mapping |
ICCV
2009
IEEE
14 years 11 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...
ESANN
2004
13 years 8 months ago
2004
: Probability distribution mapping function, which maps multivariate data distribution to the function of one variable, is introduced. Distributionmapping exponent (DME) is somethi...
CVPR
2008
IEEE
14 years 8 months ago
2008
IEEE
We consider the problem of dimensionality reduction, where given high-dimensional data we want to estimate two mappings: from high to low dimension (dimensionality reduction) and f...
PKDD
2010
Springer
13 years 4 months ago
2010
Springer
The foremost nonlinear dimensionality reduction algorithms provide an embedding only for the given training data, with no straightforward extension for test points. This shortcomin...
AAAI
2010
13 years 8 months ago
2010
Dimensionality reduction is the process by which a set of data points in a higher dimensional space are mapped to a lower dimension while maintaining certain properties of these p...