165 search results - page 12 / 33 » Adaptive dimension reduction for clustering high dimensional... |
ICCV
2003
IEEE
16 years 1 months ago
2003
IEEE
Feature space analysis is the main module in many computer vision tasks. The most popular technique, k-means clustering, however, has two inherent limitations: the clusters are co...
TSP
2010
14 years 6 months ago
2010
In this paper, we present multiple novel applications for local intrinsic dimension estimation. There has been much work done on estimating the global dimension of a data set, typi...
118
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WIRN
2005
Springer
15 years 5 months ago
2005
Springer
We present an algorithmic scheme for unsupervised cluster ensembles, based on randomized projections between metric spaces, by which a substantial dimensionality reduction is obtai...
126
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ICPP
2000
IEEE
15 years 4 months ago
2000
IEEE
Clustering is a data mining problem which finds dense regions in a sparse multi-dimensional data set. The attribute values and ranges of these regions characterize the clusters. ...
ICANN
2005
Springer
15 years 5 months ago
2005
Springer
Multidimensional Scaling (MDS) is a powerful dimension reduction technique for embedding high-dimensional data into a lowdimensional target space. Thereby, the distance relationshi...