396 search results - page 9 / 80 » Lossy Reduction for Very High Dimensional Data |
PAMI
2007
14 years 9 months ago
2007
—A new unsupervised forward orthogonal search (FOS) algorithm is introduced for feature selection and ranking. In the new algorithm, features are selected in a stepwise way, one ...
KDD
2001
ACM
15 years 9 months ago
2001
ACM
Random projections have recently emerged as a powerful method for dimensionality reduction. Theoretical results indicate that the method preserves distances quite nicely; however,...
ICML
2003
IEEE
15 years 10 months ago
2003
IEEE
We investigate how random projection can best be used for clustering high dimensional data. Random projection has been shown to have promising theoretical properties. In practice,...
ICONIP
2007
14 years 11 months ago
2007
Abstract. Principal component analysis (PCA) is a widely used technique for data analysis and dimensionality reduction. Eigenvalue decomposition is the standard algorithm for solvi...
PAMI
2006
14 years 9 months ago
2006
We provide evidence that non-linear dimensionality reduction, clustering and data set parameterization can be solved within one and the same framework. The main idea is to define ...