59 search results - page 3 / 12 » REDUS: finding reducible subspaces in high dimensional data |
ICDE
2010
IEEE
13 years 2 months ago
2010
IEEE
Abstract— We propose the Multi-resolution Correlation Cluster detection (MrCC), a novel, scalable method to detect correlation clusters able to analyze dimensional data in the ra...
CVPR
2008
IEEE
14 years 6 months ago
2008
IEEE
Nearest neighbour classifiers and related kernel methods often perform poorly in high dimensional problems because it is infeasible to include enough training samples to cover the...
ICDE
2003
IEEE
14 years 5 months ago
2003
IEEE
The notorious "dimensionality curse" is a well-known phenomenon for any multi-dimensional indexes attempting to scale up to high dimensions. One well known approach to o...
ICDM
2002
IEEE
13 years 9 months ago
2002
IEEE
It is well-known that for high dimensional data clustering, standard algorithms such as EM and the K-means are often trapped in local minimum. Many initialization methods were pro...
ICDM
2009
IEEE
13 years 2 months ago
2009
IEEE
Text classification poses some specific challenges. One such challenge is its high dimensionality where each document (data point) contains only a small subset of them. In this pap...