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» Data Mining via Support Vector Machines
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BMCBI
2007
77views more  BMCBI 2007»
14 years 10 months ago
Effective selection of informative SNPs and classification on the HapMap genotype data
Background: Since the single nucleotide polymorphisms (SNPs) are genetic variations which determine the difference between any two unrelated individuals, the SNPs can be used to i...
Nina Zhou, Lipo Wang
OSDI
2008
ACM
15 years 6 days ago
DryadLINQ: A System for General-Purpose Distributed Data-Parallel Computing Using a High-Level Language
DryadLINQ is a system and a set of language extensions that enable a new programming model for large scale distributed computing. It generalizes previous execution environments su...
Yuan Yu, Michael Isard, Dennis Fetterly, Mihai Bud...
ICDT
2001
ACM
147views Database» more  ICDT 2001»
15 years 2 months ago
Parallelizing the Data Cube
This paper presents a general methodology for the efficient parallelization of existing data cube construction algorithms. We describe two different partitioning strategies, one f...
Frank K. H. A. Dehne, Todd Eavis, Susanne E. Hambr...
ICAS
2006
IEEE
139views Robotics» more  ICAS 2006»
15 years 3 months ago
Predicting Resource Demand in Dynamic Utility Computing Environments
— We target the problem of predicting resource usage in situations where the modeling data is scarce, non-stationary, or expensive to obtain. This scenario occurs frequently in c...
Artur Andrzejak, Sven Graupner, Stefan Plantikow
ISCIS
2005
Springer
15 years 3 months ago
Classification of Volatile Organic Compounds with Incremental SVMs and RBF Networks
Support Vector Machines (SVMs) have been applied to solve the classification of volatile organic compounds (VOC) data in some recent studies. SVMs provide good generalization perfo...
Zeki Erdem, Robi Polikar, Nejat Yumusak, Fikret S....