99 search results - page 4 / 20 » Generalization of the Kantorovich Method of Dimensional Redu... |
CVPR
2008
IEEE
14 years 10 months ago
2008
IEEE
We propose a novel algorithm for clustering data sampled from multiple submanifolds of a Riemannian manifold. First, we learn a representation of the data using generalizations of...
CIKM
2003
Springer
14 years 1 months ago
2003
Springer
High dimensional data sets are encountered in many modern database applications. The usual approach is to construct a summary of the data set through a lossy compression technique...
ICML
2010
IEEE
13 years 9 months ago
2010
IEEE
Many learning applications are characterized by high dimensions. Usually not all of these dimensions are relevant and some are redundant. There are two main approaches to reduce d...
ECCV
2006
Springer
14 years 10 months ago
2006
Springer
Abstract. We present a novel method for dimensionality reduction and recognition based on Linear Discriminant Analysis (LDA), which specifically deals with the Small Sample Size (S...
CVPR
2008
IEEE
14 years 10 months ago
2008
IEEE
Linear Discriminant Analysis (LDA) is one of the wellknown methods for supervised dimensionality reduction. Over the years, many LDA-based algorithms have been developed to cope w...