26 search results - page 4 / 6 » Bayesian regression with input noise for high dimensional da... |
NIPS
2007
13 years 9 months ago
2007
Recent research has studied the role of sparsity in high dimensional regression and signal reconstruction, establishing theoretical limits for recovering sparse models from sparse...
ICCV
2009
IEEE
15 years 13 days 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...
ICPR
2006
IEEE
14 years 8 months ago
2006
IEEE
In this paper, we apply a multiple regression method based on Canonical Correlation Analysis (CCA) to face data modelling. CCA is a factor analysis method which exploits the corre...
PAMI
1998
13 years 7 months ago
1998
A new method for analyzing the intrinsic dimensionality (ID) of low dimensional manifolds in high dimensional feature spaces is presented. The basic idea is to rst extract a low-d...
CVPR
2010
IEEE
14 years 20 days 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. ...