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    BMCBI
    2008
    186views more  BMCBI 2008»
    Variable selection for large p small n regression models with incomplete data: Mapping QTL with epistases
    13 years 7 months ago
    Variable selection for large p small n regression models with incomplete data: Mapping QTL with epistases
    Download  www.biomedcentral.com
    Background: Identifying quantitative trait loci (QTL) for both additive and epistatic effects raises the statistical issue of selecting variables from a large number of candidates...
    Min Zhang, Dabao Zhang, Martin T. Wells
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    VLDB
    1998
    ACM
    180views Database» more  VLDB 1998»
    Active Storage for Large-Scale Data Mining and Multimedia
    13 years 12 months ago
    Active Storage for Large-Scale Data Mining and Multimedia
    Download  www.pdl.cmu.edu
    The increasing performance and decreasing cost of processors and memory are causing system intelligence to move into peripherals from the CPU. Storage system designers are using t...
    Erik Riedel, Garth A. Gibson, Christos Faloutsos
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    NIPS
    2008
    126views Information Technology» more  NIPS 2008»
    On the Reliability of Clustering Stability in the Large Sample Regime
    13 years 9 months ago
    On the Reliability of Clustering Stability in the Large Sample Regime
    Download  www.cs.huji.ac.il
    Clustering stability is an increasingly popular family of methods for performing model selection in data clustering. The basic idea is that the chosen model should be stable under...
    Ohad Shamir, Naftali Tishby
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    IPPS
    2008
    IEEE
    125views Distributed And Parallel Com...» more  IPPS 2008»
    High-speed string searching against large dictionaries on the Cell/B.E. Processor
    14 years 2 months ago
    High-speed string searching against large dictionaries on the Cell/B.E. Processor
    Download  domino.research.ibm.com
    Our digital universe is growing, creating exploding amounts of data which need to be searched, protected and filtered. String searching is at the core of the tools we use to curb...
    Daniele Paolo Scarpazza, Oreste Villa, Fabrizio Pe...
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    SDM
    2004
    SIAM
    211views Data Mining» more  SDM 2004»
    Using Support Vector Machines for Classifying Large Sets of Multi-Represented Objects
    13 years 9 months ago
    Using Support Vector Machines for Classifying Large Sets of Multi-Represented Objects
    Download  www.dbs.informatik.uni-muenchen.de
    Databases are a key technology for molecular biology which is a very data intensive discipline. Since molecular biological databases are rather heterogeneous, unification and data...
    Hans-Peter Kriegel, Peer Kröger, Alexey Pryak...
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