1224 search results - page 2 / 245 » On the Optimality of the Dimensionality Reduction Method |
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...
ICML
2010
IEEE
13 years 6 months ago
2010
IEEE
Many learning applications are characterized by high dimensions. Usually not all of these dimensions are relevant and some are redundant. There are two main approaches to reduce d...
CVPR
2009
IEEE
15 years 13 days ago
2009
IEEE
Non-linear dimensionality reductionmethods are powerful techniques to deal with
high-dimensional datasets. However, they often are susceptible to local minima
and perform poorly ...
SIAMSC
2008
13 years 5 months ago
2008
A model-constrained adaptive sampling methodology is proposed for reduction of large-scale systems with high-dimensional parametric input spaces. Our model reduction method uses a ...
JMLR
2010
13 years 3 months ago
2010
Nonlinear dimensionality reduction methods are often used to visualize high-dimensional data, although the existing methods have been designed for other related tasks such as mani...