12 search results - page 2 / 3 » Parametric Dimensionality Reduction by Unsupervised Regressi... |
PKDD
2010
Springer
13 years 2 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...
ICCV
2009
IEEE
14 years 10 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...
CVPR
2010
IEEE
13 years 10 months ago
2010
IEEE
Non-negative matrix factorization (NMF) is an excellent tool for unsupervised parts-based learning, but proves to be ineffective when parts of a whole follow a specific pattern. ...
ICIP
2007
IEEE
13 years 9 months ago
2007
IEEE
This communication deals with data reduction and regression. A set of high dimensional data (e.g., images) usually has only a few degrees of freedom with corresponding variables t...
BMVC
2010
13 years 3 months ago
2010
This paper explores a recently proposed and rarely reported subspace learning method, Spectral Regression Discriminant Analysis (SRDA) [1, 2], on silhouette based human action rec...