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» Clustering performance data efficiently at massive scales
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ESANN
2008
14 years 11 months ago
Parallelizing single patch pass clustering
Clustering algorithms such as k-means, the self-organizing map (SOM), or Neural Gas (NG) constitute popular tools for automated information analysis. Since data sets are becoming l...
Nikolai Alex, Barbara Hammer
CLUSTER
2006
IEEE
15 years 1 months ago
Lightweight I/O for Scientific Applications
Today's high-end massively parallel processing (MPP) machines have thousands to tens of thousands of processors, with next-generation systems planned to have in excess of one...
Ron Oldfield, Lee Ward, Rolf Riesen, Arthur B. Mac...
JMLR
2010
130views more  JMLR 2010»
14 years 4 months ago
MOA: Massive Online Analysis, a Framework for Stream Classification and Clustering
Massive Online Analysis (MOA) is a software environment for implementing algorithms and running experiments for online learning from evolving data streams. MOA is designed to deal...
Albert Bifet, Geoff Holmes, Bernhard Pfahringer, P...
DBISP2P
2004
Springer
162views Database» more  DBISP2P 2004»
15 years 2 months ago
CISS: An Efficient Object Clustering Framework for DHT-Based Peer-to-Peer Applications
Distributed Hash Tables (DHTs) have been widely adopted in many Internet-scale P2P systems. Emerging P2P applications such as massively multi player online games (MMOGs) and P2P ca...
Jinwon Lee, Hyonik Lee, Seungwoo Kang, Sungwon Pet...
PAMI
2010
119views more  PAMI 2010»
14 years 8 months ago
Efficient Multilevel Eigensolvers with Applications to Data Analysis Tasks
—Multigrid solvers proved very efficient for solving massive systems of equations in various fields. These solvers are based on iterative relaxation schemes together with the app...
Dan Kushnir, Meirav Galun, Achi Brandt