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» Algorithms for Clustering Data
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PODS
2003
ACM
143views Database» more  PODS 2003»
16 years 7 months ago
Maintaining variance and k-medians over data stream windows
The sliding window model is useful for discounting stale data in data stream applications. In this model, data elements arrive continually and only the most recent N elements are ...
Brian Babcock, Mayur Datar, Rajeev Motwani, Liadan...
GECCO
2007
Springer
162views Optimization» more  GECCO 2007»
16 years 1 months ago
A multi-objective approach to discover biclusters in microarray data
The main motivation for using a multi–objective evolutionary algorithm for finding biclusters in gene expression data is motivated by the fact that when looking for biclusters ...
Federico Divina, Jesús S. Aguilar-Ruiz
ESA
2003
Springer
123views Algorithms» more  ESA 2003»
16 years 8 days ago
Experiments on Graph Clustering Algorithms
A promising approach to graph clustering is based on the intuitive notion of intra-cluster density vs. inter-cluster sparsity. While both formalizations and algorithms focusing on ...
Ulrik Brandes, Marco Gaertler, Dorothea Wagner
ICTAI
2008
IEEE
16 years 1 months ago
Veritas: Combining Expert Opinions without Labeled Data
We consider a variation of the problem of combining expert opinions for the situation in which there is no ground truth to use for training. Even though we don’t have labeled da...
Sharath R. Cholleti, Sally A. Goldman, Avrim Blum,...
MIDDLEWARE
2007
Springer
16 years 1 months ago
New Worker-Centric Scheduling Strategies for Data-Intensive Grid Applications
Distributed computations, dealing with large amounts of data, are scheduled in Grid clusters today using either a task-centric mechanism, or a worker-centric mechanism. Because of ...
Steven Y. Ko, Ramsés Morales, Indranil Gupt...