434 search results - page 37 / 87 » Dimensionality Reduction of Clustered Data Sets |
MLDM
2005
Springer
14 years 2 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...
CEC
2005
IEEE
14 years 2 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 ...
JCP
2007
13 years 8 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....
ICTAI
2006
IEEE
14 years 2 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...
ICML
2007
IEEE
14 years 9 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...