434 search results - page 37 / 87 » Dimensionality Reduction of Clustered Data Sets |
130
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MLDM
2005
Springer
15 years 9 months ago
2005
Springer
Subspace clustering is an extension of traditional clustering that seeks to find clusters in different subspaces within a dataset. This is a particularly important challenge with...
129
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CEC
2005
IEEE
15 years 10 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 ...
144
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JCP
2007
15 years 4 months ago
2007
Abstract— Analyzing unknown data sets such as multispectral images often requires unsupervised techniques. Data clustering is a well known and widely used approach in such cases....
131
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ICTAI
2006
IEEE
15 years 10 months ago
2006
IEEE
We propose two Euclidean minimum spanning tree based clustering algorithms — one a k-constrained, and the other an unconstrained algorithm. Our k-constrained clustering algorith...
141
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ICML
2007
IEEE
16 years 5 months ago
2007
IEEE
The Gaussian process latent variable model (GP-LVM) is a powerful approach for probabilistic modelling of high dimensional data through dimensional reduction. In this paper we ext...