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» Clustering of Self-Organizing Map
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COMPGEOM
2011
ACM
12 years 11 months ago
Persistence-based clustering in riemannian manifolds
We present a clustering scheme that combines a mode-seeking phase with a cluster merging phase in the corresponding density map. While mode detection is done by a standard graph-b...
Frédéric Chazal, Leonidas J. Guibas,...
ISLPED
2005
ACM
93views Hardware» more  ISLPED 2005»
14 years 1 months ago
Power-aware code scheduling for clusters of active disks
In this paper, we take the idea of application-level processing on disks to one level further, and focus on an architecture, called Cluster of Active Disks (CAD), where the storag...
Seung Woo Son, Guangyu Chen, Mahmut T. Kandemir
BMCBI
2002
195views more  BMCBI 2002»
13 years 7 months ago
Clustering of the SOM easily reveals distinct gene expression patterns: results of a reanalysis of lymphoma study
Background: A method to evaluate and analyze the massive data generated by series of microarray experiments is of utmost importance to reveal the hidden patterns of gene expressio...
Junbai Wang, Jan Delabie, Hans Christian Aasheim, ...
CVPR
2004
IEEE
14 years 10 months ago
Model-Based Motion Clustering Using Boosted Mixture Modeling
Model-based clustering of motion trajectories can be posed as the problem of learning an underlying mixture density function whose components correspond to motion classes with dif...
Vladimir Pavlovic
BIBE
2008
IEEE
142views Bioinformatics» more  BIBE 2008»
14 years 2 months ago
Optimizing performance, cost, and sensitivity in pairwise sequence search on a cluster of PlayStations
— The Smith-Waterman algorithm is a dynamic programming method for determining optimal local alignments between nucleotide or protein sequences. However, it suffers from quadrati...
Ashwin M. Aji, Wu-chun Feng