298 search results - page 27 / 60 » Subspace Clustering of High Dimensional Data |
146
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KDD
2008
ACM
16 years 26 days ago
2008
ACM
The success of popular algorithms such as k-means clustering or nearest neighbor searches depend on the assumption that the underlying distance functions reflect domain-specific n...
112
Voted
MICAI
2005
Springer
15 years 6 months ago
2005
Springer
Abstract. Kernel based methods (such as k-nearest neighbors classifiers) for AI tasks translate the classification problem into a proximity search problem, in a space that is usu...
97
Voted
CVPR
2005
IEEE
16 years 2 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...
172
Voted
KDD
2000
ACM
15 years 4 months ago
2000
ACM
The grand tour, one of the most popular methods for multidimensional data exploration, is based on orthogonally projecting multidimensional data to a sequence of lower dimensional...
138
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EDBT
1998
ACM
15 years 4 months ago
1998
ACM
Abstract. In this paper, we propose a new bulk-loading technique for high-dimensional indexes which represent an important component of multimedia database systems. Since it is ver...