165 search results - page 14 / 33 » Adaptive dimension reduction for clustering high dimensional... |
FGR
2006
IEEE
15 years 5 months ago
2006
IEEE
We propose an Isometric Self-Organizing Map (ISOSOM) method for nonlinear dimensionality reduction, which integrates a Self-Organizing Map model and an ISOMAP dimension reduction ...
172
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ICML
2004
IEEE
16 years 16 days ago
2004
IEEE
Principal component analysis (PCA) is a widely used statistical technique for unsupervised dimension reduction. K-means clustering is a commonly used data clustering for unsupervi...
119
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SIGMOD
2001
ACM
15 years 12 months ago
2001
ACM
Similarity search in large time series databases has attracted much research interest recently. It is a difficult problem because of the typically high dimensionality of the data....
111
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KDD
2004
ACM
16 years 3 days ago
2004
ACM
Recent years have witnessed a dramatic increase in the quantity of image data collected, due to advances in fields such as medical imaging, reconnaissance, surveillance, astronomy...
ICML
2007
IEEE
16 years 16 days ago
2007
IEEE
We study the problem of discovering a manifold that best preserves information relevant to a nonlinear regression. Solving this problem involves extending and uniting two threads ...