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» Computing LTS Regression for Large Data Sets
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ICML
2008
IEEE
14 years 10 months ago
Fully distributed EM for very large datasets
In EM and related algorithms, E-step computations distribute easily, because data items are independent given parameters. For very large data sets, however, even storing all of th...
Jason Wolfe, Aria Haghighi, Dan Klein
CSDA
2006
98views more  CSDA 2006»
13 years 9 months ago
Fast estimation algorithm for likelihood-based analysis of repeated categorical responses
Likelihood-based marginal regression modelling for repeated, or otherwise clustered, categorical responses is computationally demanding. This is because the number of measures nee...
Jukka Jokinen
APVIS
2007
13 years 10 months ago
A comparison of vertex ordering algorithms for large graph visualization
In this study, we examine the use of graph ordering algorithms for visual analysis of data sets using visual similarity matrices. Visual similarity matrices display the relationsh...
Christopher Mueller, Benjamin Martin, Andrew Lumsd...
SIGMOD
2004
ACM
92views Database» more  SIGMOD 2004»
14 years 9 months ago
Online Maintenance of Very Large Random Samples
Random sampling is one of the most fundamental data management tools available. However, most current research involving sampling considers the problem of how to use a sample, and...
Chris Jermaine, Abhijit Pol, Subramanian Arumugam
ICDE
2007
IEEE
218views Database» more  ICDE 2007»
14 years 10 months ago
SKYPEER: Efficient Subspace Skyline Computation over Distributed Data
Skyline query processing has received considerable attention in the recent past. Mainly, the skyline query is used to find a set of non dominated data points in a multidimensional...
Akrivi Vlachou, Christos Doulkeridis, Yannis Kotid...