3006 search results - page 31 / 602 » Dimensionality reduction and generalization |
NIPS
2003
13 years 10 months ago
2003
We propose a novel method of dimensionality reduction for supervised learning. Given a regression or classification problem in which we wish to predict a variable Y from an expla...
PKDD
2010
Springer
13 years 6 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...
COMSIS
2010
13 years 6 months ago
2010
Dimensionality reduction is an important preprocessing step in high-dimensional data analysis without losing intrinsic information. The problem of semi-supervised nonlinear dimensi...
ICA
2004
Springer
14 years 2 months ago
2004
Springer
In usual ICA methods, sources are typically estimated by maximizing a measure of their statistical independence. This paper explains how to perform non-linear ICA by preprocessing ...
ESANN
2008
13 years 10 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, ...