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» A Method for Dynamic Clustering of Data
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ICML
2007
IEEE
16 years 5 months ago
A permutation-augmented sampler for DP mixture models
We introduce a new inference algorithm for Dirichlet process mixture models. While Gibbs sampling and variational methods focus on local moves, the new algorithm makes more global...
Percy Liang, Michael I. Jordan, Benjamin Taskar
ICIP
2002
IEEE
15 years 9 months ago
Two channels fuzzy c-means detection of multiple sclerosis lesions in multispectral MR images
A novel approach to the detection of multiple sclerosis (MS) lesions in T2- and PD-weighted MR images is presented. The core of the proposed method is the use of the two channels ...
Daniele Peri, Edoardo Ardizzone, Roberto Pirrone, ...
IPPS
2006
IEEE
15 years 10 months ago
Dynamic resource allocation of computer clusters with probabilistic workloads
Real-time resource scheduling is an important factor for improving the performance of cluster computing. In many distributed and parallel processing systems, particularly real-tim...
Marwan S. Sleiman, Lester Lipsky, Robert Sheahan
BMCBI
2008
104views more  BMCBI 2008»
15 years 4 months ago
Missing value imputation improves clustering and interpretation of gene expression microarray data
Background: Missing values frequently pose problems in gene expression microarray experiments as they can hinder downstream analysis of the datasets. While several missing value i...
Johannes Tuikkala, Laura Elo, Olli Nevalainen, Ter...
CSDA
2008
91views more  CSDA 2008»
15 years 4 months ago
Model-based clustering for longitudinal data
A model-based clustering method is proposed for clustering individuals on the basis of measurements taken over time. Data variability is taken into account through non-linear hier...
Rolando De la Cruz-Mesía, Fernando A. Quint...