576 search results - page 21 / 116 » Structured metric learning for high dimensional problems |
UAI
2001
13 years 9 months ago
2001
A serious problem in learning probabilistic models is the presence of hidden variables. These variables are not observed, yet interact with several of the observed variables. Dete...
ACCV
2009
Springer
14 years 2 months ago
2009
Springer
This paper develops a supervised dimensionality reduction method, Lorentzian Discriminant Projection (LDP), for discriminant analysis and classification. Our method represents the...
ECCV
2006
Springer
14 years 9 months ago
2006
Springer
In recent years, nonlinear dimensionality reduction (NLDR) techniques have attracted much attention in visual perception and many other areas of science. We propose an efficient al...
JMLR
2012
11 years 10 months ago
2012
Often when modeling structured domains, it is desirable to leverage information that is not naturally expressed as simply a label. Examples include knowledge about the evaluation ...
NIPS
2004
13 years 9 months ago
2004
Many machine learning algorithms for clustering or dimensionality reduction take as input a cloud of points in Euclidean space, and construct a graph with the input data points as...