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BMCBI
2007
123views more  BMCBI 2007»
13 years 10 months ago
Robust clustering in high dimensional data using statistical depths
Background: Mean-based clustering algorithms such as bisecting k-means generally lack robustness. Although componentwise median is a more robust alternative, it can be a poor cent...
Yuanyuan Ding, Xin Dang, Hanxiang Peng, Dawn Wilki...
VIS
2008
IEEE
204views Visualization» more  VIS 2008»
14 years 11 months ago
Surface Extraction from Multi-field Particle Volume Data Using Multi-dimensional Cluster Visualization
Data sets resulting from physical simulations typically contain a multitude of physical variables. It is, therefore, desirable that visualization methods take into account the enti...
Lars Linsen, Tran Van Long, Paul Rosenthal, Ste...
CLASSIFICATION
2006
108views more  CLASSIFICATION 2006»
13 years 10 months ago
The Practice of Cluster Analysis
Abstracts "Mixtures at the Interface" David Scott, Rice University Mixture modeling provides an effective framework for complex, high-dimensional data. The potential of m...
Jon R. Kettenring
EDBT
2004
ACM
89views Database» more  EDBT 2004»
14 years 10 months ago
Management of Highly Dynamic Multidimensional Data in a Cluster of Workstations
Vassil Kriakov, Alex Delis, George Kollios
CORR
2011
Springer
151views Education» more  CORR 2011»
13 years 5 months ago
A supervised clustering approach for fMRI-based inference of brain states
We propose a method that combines signals from many brain regions observed in functional Magnetic Resonance Imaging (fMRI) to predict the subject’s behavior during a scanning se...
Vincent Michel, Alexandre Gramfort, Gaël Varo...