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LWA
2008
15 years 8 months ago
Pre analysis and clustering of uncertain data from manufacturing processes
With increasing complexity of manufacturing processes, the volume of data that has to be evaluated rises accordingly. The complexity and data volume make any kind of manual data a...
Peter Benjamin Volk, Martin Hahmann, Dirk Habich, ...
CLASSIFICATION
2007
105views more  CLASSIFICATION 2007»
15 years 6 months ago
Bayesian Regularization for Normal Mixture Estimation and Model-Based Clustering
Normal mixture models are widely used for statistical modeling of data, including cluster analysis. However maximum likelihood estimation (MLE) for normal mixtures using the EM al...
Chris Fraley, Adrian E. Raftery
SODA
2012
ACM
223views Algorithms» more  SODA 2012»
13 years 9 months ago
Data reduction for weighted and outlier-resistant clustering
Statistical data frequently includes outliers; these can distort the results of estimation procedures and optimization problems. For this reason, loss functions which deemphasize ...
Dan Feldman, Leonard J. Schulman
ICPR
2006
IEEE
16 years 7 months ago
Learning Wormholes for Sparsely Labelled Clustering
Distance functions are an important component in many learning applications. However, the correct function is context dependent, therefore it is advantageous to learn a distance f...
Eng-Jon Ong, Richard Bowden
IPPS
2006
IEEE
16 years 22 days 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