434 search results - page 14 / 87 » Dimensionality Reduction of Clustered Data Sets |
DEXA
2006
Springer
14 years 7 days ago
2006
Springer
Abstract. Nearest neighbor search has a wide variety of applications. Unfortunately, the majority of search methods do not scale well with dimensionality. Recent efforts have been ...
AUSAI
2006
Springer
14 years 9 days ago
2006
Springer
In this paper, we propose the Kernel Laplacian Eigenmaps for nonlinear dimensionality reduction. This method can be extended to any structured input beyond the usual vectorial data...
ESANN
2004
13 years 10 months ago
2004
: Probability distribution mapping function, which maps multivariate data distribution to the function of one variable, is introduced. Distributionmapping exponent (DME) is somethi...
WEBI
2010
Springer
13 years 6 months ago
2010
Springer
High-dimensional data usually incur learning deficiencies and computational difficulties. We present a novel semi-supervised dimensionality reduction technique that embeds high-dim...
APWEB
2006
Springer
14 years 9 days ago
2006
Springer
Clustering is to identify densely populated subgroups in data, while correlation analysis is to find the dependency between the attributes of the data set. In this paper, we combin...