59 search results - page 5 / 12 » REDUS: finding reducible subspaces in high dimensional data |
HAIS
2009
Springer
13 years 10 months ago
2009
Springer
Developing models and methods to manage data vagueness is a current effervescent research field. Some work has been done with supervised problems but unsupervised problems and unce...
ICCV
2007
IEEE
14 years 7 months ago
2007
IEEE
Most existing subspace analysis-based tracking algorithms utilize a flattened vector to represent a target, resulting in a high dimensional data learning problem. Recently, subspa...
VLDB
2000
ACM
13 years 9 months ago
2000
ACM
Many emerging application domains require database systems to support efficient access over highly multidimensional datasets. The current state-of-the-art technique to indexing hi...
CVPR
2005
IEEE
14 years 7 months ago
2005
IEEE
In this paper we focus on high dimensional data sets for which the number of dimensions is an order of magnitude higher than the number of objects. From a classifier design standp...
ICDE
1997
IEEE
14 years 6 months ago
1997
IEEE
Many emerging data mining applications require a similarity join between points in a high-dimensional domain. We present a new algorithm that utilizes a new index structure, calle...