3006 search results - page 27 / 602 » Dimensionality reduction and generalization |
AAAI
2010
13 years 10 months ago
2010
Multi-instance learning deals with problems that treat bags of instances as training examples. In single-instance learning problems, dimensionality reduction is an essential step ...
CVPR
2006
IEEE
14 years 10 months ago
2006
IEEE
Dimensionality reduction involves mapping a set of high dimensional input points onto a low dimensional manifold so that "similar" points in input space are mapped to ne...
ICIP
2007
IEEE
14 years 10 months ago
2007
IEEE
Image segmentation with shape priors has received a lot of attention over the past years. Most existing work focuses on a linearized shape space with small deformation modes aroun...
COMPGEOM
2009
ACM
14 years 3 months ago
2009
ACM
Nonlinear dimensionality reduction (NLDR) algorithms such as Isomap, LLE and Laplacian Eigenmaps address the problem of representing high-dimensional nonlinear data in terms of lo...
VISSYM
2003
13 years 10 months ago
2003
Traditional visualization techniques for multidimensional data sets, such as parallel coordinates, glyphs, and scatterplot matrices, do not scale well to high numbers of dimension...