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» Deterministic algorithms for sampling count data
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COMPGEOM
2004
ACM
13 years 10 months ago
Range counting over multidimensional data streams
We consider the problem of approximate range counting over streams of d-dimensional points. In the data stream model, the algorithm makes a single scan of the data, which is prese...
Subhash Suri, Csaba D. Tóth, Yunhong Zhou
NPL
2000
95views more  NPL 2000»
13 years 5 months ago
Bayesian Sampling and Ensemble Learning in Generative Topographic Mapping
Generative topographic mapping (GTM) is a statistical model to extract a hidden smooth manifold from data, like the self-organizing map (SOM). Although a deterministic search algo...
Akio Utsugi
ICDM
2002
IEEE
448views Data Mining» more  ICDM 2002»
13 years 10 months ago
Feature Selection Algorithms: A Survey and Experimental Evaluation
In view of the substantial number of existing feature selection algorithms, the need arises to count on criteria that enables to adequately decide which algorithm to use in certai...
Luis Carlos Molina, Lluís Belanche, À...
BMCBI
2010
147views more  BMCBI 2010»
13 years 5 months ago
baySeq: Empirical Bayesian methods for identifying differential expression in sequence count data
Background: High throughput sequencing has become an important technology for studying expression levels in many types of genomic, and particularly transcriptomic, data. One key w...
Thomas J. Hardcastle, Krystyna A. Kelly
WWW
2008
ACM
14 years 6 months ago
Learning deterministic regular expressions for the inference of schemas from XML data
Inferring an appropriate DTD or XML Schema Definition (XSD) for a given collection of XML documents essentially reduces to learning deterministic regular expressions from sets of ...
Geert Jan Bex, Wouter Gelade, Frank Neven, Stijn V...