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» Approximation algorithms for clustering uncertain data
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SBBD
2000
168views Database» more  SBBD 2000»
13 years 9 months ago
Fast Feature Selection Using Fractal Dimension
Dimensionalitycurse and dimensionalityreduction are two issues that have retained highinterest for data mining, machine learning, multimedia indexing, and clustering. We present a...
Caetano Traina Jr., Agma J. M. Traina, Leejay Wu, ...
ESA
2005
Springer
123views Algorithms» more  ESA 2005»
14 years 1 months ago
Oblivious vs. Distribution-Based Sorting: An Experimental Evaluation
We compare two algorithms for sorting out-of-core data on a distributed-memory cluster. One algorithm, Csort, is a 3-pass oblivious algorithm. The other, Dsort, makes three passes...
Geeta Chaudhry, Thomas H. Cormen
GIS
2008
ACM
14 years 8 months ago
Parallel ODETLAP for terrain compression and reconstruction
We introduce a parallel approximation of an Over-determined Laplacian Partial Differential Equation solver (ODETLAP) applied to the compression and restoration of terrain data use...
Jared Stookey, Zhongyi Xie, Barbara Cutler, W. Ran...
BMCBI
2010
138views more  BMCBI 2010»
13 years 7 months ago
UFFizi: a generic platform for ranking informative features
Background: Feature selection is an important pre-processing task in the analysis of complex data. Selecting an appropriate subset of features can improve classification or cluste...
Assaf Gottlieb, Roy Varshavsky, Michal Linial, Dav...
WWW
2010
ACM
14 years 2 months ago
Sampling community structure
We propose a novel method, based on concepts from expander graphs, to sample communities in networks. We show that our sampling method, unlike previous techniques, produces subgra...
Arun S. Maiya, Tanya Y. Berger-Wolf