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ICDM
2003
IEEE
112views Data Mining» more  ICDM 2003»
14 years 19 days ago
Privacy-preserving Distributed Clustering using Generative Models
We present a framework for clustering distributed data in unsupervised and semi-supervised scenarios, taking into account privacy requirements and communication costs. Rather than...
Srujana Merugu, Joydeep Ghosh
ICPR
2008
IEEE
14 years 8 months ago
K-means clustering of proportional data using L1 distance
We present a new L1-distance-based k-means clustering algorithm to address the challenge of clustering high-dimensional proportional vectors. The new algorithm explicitly incorpor...
Bonnie K. Ray, Hisashi Kashima, Jianying Hu, Monin...
IJCAI
2003
13 years 8 months ago
Distributed Clustering Based on Sampling Local Density Estimates
Huge amounts of data are stored in autonomous, geographically distributed sources. The discovery of previously unknown, implicit and valuable knowledge is a key aspect of the expl...
Matthias Klusch, Stefano Lodi, Gianluca Moro
EUROPAR
1999
Springer
13 years 11 months ago
Parallel k/h-Means Clustering for Large Data Sets
This paper describes the realization of a parallel version of the k/h-means clustering algorithm. This is one of the basic algorithms used in a wide range of data mining tasks. We ...
Kilian Stoffel, Abdelkader Belkoniene
DNIS
2010
Springer
184views Database» more  DNIS 2010»
14 years 1 months ago
A Study on Workload Imbalance Issues in Data Intensive Distributed Computing
In recent years, several frameworks have been developed for processing very large quantities of data on large clusters of commodity PCs. These frameworks have focused on fault-tole...
Sven Groot, Kazuo Goda, Masaru Kitsuregawa