103 search results - page 10 / 21 » Projective ART for clustering data sets in high dimensional ... |
DASFAA
2007
IEEE
14 years 1 months ago
2007
IEEE
Subspace clustering (also called projected clustering) addresses the problem that different sets of attributes may be relevant for different clusters in high dimensional feature sp...
ICCV
2009
IEEE
15 years 11 days ago
2009
IEEE
We present a manifold learning approach to dimensionality
reduction that explicitly models the manifold as a mapping
from low to high dimensional space. The manifold is
represen...
CORR
1999
Springer
13 years 7 months ago
1999
Springer
Abstract. Nearest neighbor searching is a fundamental computational problem. A set of n data points is given in real d-dimensional space, and the problem is to preprocess these poi...
ICDM
2007
IEEE
14 years 1 months ago
2007
IEEE
Support vector clustering transforms the data into a high dimensional feature space, where a decision function is computed. In the original space, the function outlines the bounda...
CEC
2005
IEEE
14 years 1 months ago
2005
IEEE
In previous work, we have proposed a novel approach to data clustering based on the explicit optimization of a partitioning with respect to two complementary clustering objectives ...