434 search results - page 17 / 87 » Dimensionality Reduction of Clustered Data Sets |
BMCBI
2007
13 years 8 months ago
2007
Background: Mean-based clustering algorithms such as bisecting k-means generally lack robustness. Although componentwise median is a more robust alternative, it can be a poor cent...
29
Voted
KDD
2010
ACM
13 years 10 months ago
2010
ACM
Dimensionality reduction plays an important role in many data mining applications involving high-dimensional data. Many existing dimensionality reduction techniques can be formula...
CIKM
2003
Springer
14 years 1 months ago
2003
Springer
High dimensional data sets are encountered in many modern database applications. The usual approach is to construct a summary of the data set through a lossy compression technique...
CVPR
2006
IEEE
14 years 10 months ago
2006
IEEE
Dimensionality reduction involves mapping a set of high dimensional input points onto a low dimensional manifold so that "similar" points in input space are mapped to ne...
EDBT
2006
ACM
14 years 7 days ago
2006
ACM
Utilizing spatial index structures on secondary memory for nearest neighbor search in high-dimensional data spaces has been the subject of much research. With the potential to host...