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ICDE
2003
IEEE
116views Database» more  ICDE 2003»
14 years 9 months ago
Joining Massive High-Dimensional Datasets
We consider the problem of joining massive datasets. We propose two techniques for minimizing disk I/O cost of join operations for both spatial and sequence data. Our techniques o...
Tamer Kahveci, Christian A. Lang, Ambuj K. Singh
WIRN
2005
Springer
14 years 1 months ago
Ensembles Based on Random Projections to Improve the Accuracy of Clustering Algorithms
We present an algorithmic scheme for unsupervised cluster ensembles, based on randomized projections between metric spaces, by which a substantial dimensionality reduction is obtai...
Alberto Bertoni, Giorgio Valentini
ECEASST
2010
13 years 5 months ago
Self Organized Swarms for cluster preserving Projections of high-dimensional Data
: A new approach for topographic mapping, called Swarm-Organized Projection (SOP) is presented. SOP has been inspired by swarm intelligence methods for clustering and is similar to...
Alfred Ultsch, Lutz Herrmann
BIOINFORMATICS
2006
85views more  BIOINFORMATICS 2006»
13 years 7 months ago
Clusterv: a tool for assessing the reliability of clusters discovered in DNA microarray data
Summary: We present a new R package for the assessment of the reliability of clusters discovered in high dimensional DNA microarray data. The package implements methods based on r...
Giorgio Valentini
ICML
2006
IEEE
14 years 8 months ago
Discriminative cluster analysis
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...
Fernando De la Torre, Takeo Kanade