169 search results - page 7 / 34 » Reductions among high dimensional proximity problems |
PR
2008
13 years 7 months ago
2008
7 Linear discriminant analysis (LDA) is a dimension reduction method which finds an optimal linear transformation that maximizes the class separability. However, in undersampled p...
JMLR
2010
13 years 2 months ago
2010
Different aspects of the curse of dimensionality are known to present serious challenges to various machine-learning methods and tasks. This paper explores a new aspect of the dim...
ICPR
2010
IEEE
14 years 2 months ago
2010
IEEE
We consider the problem of classification in nonadaptive dimensionality reduction. Specifically, we bound the increase in classification error of Fisher’s Linear Discriminant...
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...
CVPR
2006
IEEE
14 years 9 months ago
2006
IEEE
Dimensionality reduction involves mapping a set of high dimensional input points onto a low dimensional manifold so that "similar" points in input space are mapped to ne...