24 search results - page 4 / 5 » A kernel view of the dimensionality reduction of manifolds |
ECCV
2002
Springer
14 years 9 months ago
2002
Springer
A visual representation of an object must meet at least three basic requirements. First, it must allow identification of the object in the presence of slight but unpredictable chan...
PR
2010
13 years 5 months ago
2010
We develop a supervised dimensionality reduction method, called Lorentzian Discriminant Projection (LDP), for feature extraction and classification. Our method represents the str...
MM
2005
ACM
14 years 27 days ago
2005
ACM
Learning the user’s semantics for CBIR involves two different sources of information: the similarity relations entailed by the content-based features, and the relevance relatio...
KDD
2007
ACM
14 years 7 months ago
2007
ACM
A good distance metric is crucial for many data mining tasks. To learn a metric in the unsupervised setting, most metric learning algorithms project observed data to a lowdimensio...
IVC
2007
13 years 7 months ago
2007
- Canonical correlation analysis (CCA) is a major linear subspace approach to dimensionality reduction and has been applied to image processing, pose estimation and other fields. H...