165 search results - page 18 / 33 » Adaptive dimension reduction for clustering high dimensional... |
IEEEMM
2007
14 years 11 months ago
2007
— Microarray technology offers a high throughput means to study expression networks and gene regulatory networks in cells. The intrinsic nature of high dimensionality and small s...
104
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ICML
2006
IEEE
16 years 15 days ago
2006
IEEE
Clustering is one of the most widely used statistical tools for data analysis. Among all existing clustering techniques, k-means is a very popular method because of its ease of pr...
106
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BMVC
2010
14 years 9 months ago
2010
We present a framework for the reduction of dimensionality of a data set via manifold learning. Using the building blocks of local hyperplanes we show how a global manifold can be...
103
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NN
2010
Springer
14 years 10 months ago
2010
Springer
The ratio of two probability density functions is becoming a quantity of interest these days in the machine learning and data mining communities since it can be used for various d...
SDM
2009
SIAM
15 years 9 months ago
2009
SIAM
In high dimensional data, the general performance of traditional clustering algorithms decreases. This is partly because the similarity criterion used by these algorithms becomes ...