166 search results - page 16 / 34 » Learning a kernel matrix for nonlinear dimensionality reduct... |
PR
2006
13 years 7 months ago
2006
In the past few years, some nonlinear dimensionality reduction (NLDR) or nonlinear manifold learning methods have aroused a great deal of interest in the machine learning communit...
IVC
2007
13 years 7 months ago
2007
Many natural image sets are samples of a low-dimensional manifold in the space of all possible images. When the image data set is not a linear combination of a small number of bas...
IJCAI
2007
13 years 9 months ago
2007
In recent years, metric learning in the semisupervised setting has aroused a lot of research interests. One type of semi-supervised metric learning utilizes supervisory informatio...
BMCBI
2010
13 years 7 months ago
2010
Background: Recent advances in proteomics technologies such as SELDI-TOF mass spectrometry has shown promise in the detection of early stage cancers. However, dimensionality reduc...
ICIP
2007
IEEE
13 years 11 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...