434 search results - page 48 / 87 » Dimensionality Reduction of Clustered Data Sets |
ICANN
2003
Springer
14 years 1 months ago
2003
Springer
Locally linear embedding (LLE) is a recently proposed method for unsupervised nonlinear dimensionality reduction. It has a number of attractive features: it does not require an ite...
SDM
2007
SIAM
13 years 10 months ago
2007
SIAM
In recent years, privacy preserving data mining has become very important because of the proliferation of large amounts of data on the internet. Many data sets are inherently high...
KDD
2008
ACM
14 years 9 months ago
2008
ACM
The success of popular algorithms such as k-means clustering or nearest neighbor searches depend on the assumption that the underlying distance functions reflect domain-specific n...
KDD
2004
ACM
14 years 9 months ago
2004
ACM
We use clustering to derive new relations which augment database schema used in automatic generation of predictive features in statistical relational learning. Clustering improves...
EDBT
2000
ACM
14 years 1 months ago
2000
ACM
In high-dimensional query processing, the optimization of the logical page-size of index structures is an important research issue. Even very simple query processing techniques suc...