166 search results - page 26 / 34 » Learning a kernel matrix for nonlinear dimensionality reduct... |
GRC
2008
IEEE
13 years 8 months ago
2008
IEEE
Manifold learning can discover the structure of high dimensional data and provides understanding of multidimensional patterns by preserving the local geometric characteristics. Ho...
ICML
2006
IEEE
14 years 8 months ago
2006
IEEE
Clustering is one of the most widely used statistical tools for data analysis. Among all existing clustering techniques, k-means is a very popular method because of its ease of pr...
FLAIRS
2004
13 years 9 months ago
2004
One important feature of the gene expression data is that the number of genes M far exceeds the number of samples N. Standard statistical methods do not work well when N < M. D...
ISVC
2010
Springer
13 years 6 months ago
2010
Springer
Abstract. We present a framework for combining automated and interactive visual analysis techniques for use on high-resolution biomechanical data. Analyzing the complex 3D motion o...
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...