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    BMCBI
    2008
    123views more  BMCBI 2008»
    Pol II promoter prediction using characteristic 4-mer motifs: a machine learning approach
    13 years 8 months ago
    Pol II promoter prediction using characteristic 4-mer motifs: a machine learning approach
    Download  www.biomedcentral.com
    Background: Eukaryotic promoter prediction using computational analysis techniques is one of the most difficult jobs in computational genomics that is essential for constructing a...
    Firoz Anwar, Syed Murtuza Baker, Taskeed Jabid, Md...
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    SIGIR
    2008
    ACM
    150views Information Technology» more  SIGIR 2008»
    Learning from labeled features using generalized expectation criteria
    13 years 8 months ago
    Learning from labeled features using generalized expectation criteria
    Download  www.cs.umass.edu
    It is difficult to apply machine learning to new domains because often we lack labeled problem instances. In this paper, we provide a solution to this problem that leverages domai...
    Gregory Druck, Gideon S. Mann, Andrew McCallum
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    LREC
    2008
    120views Education» more  LREC 2008»
    The U.S. Policy Agenda Legislation Corpus Volume 1 - a Language Resource from 1947 - 1998
    13 years 10 months ago
    The U.S. Policy Agenda Legislation Corpus Volume 1 - a Language Resource from 1947 - 1998
    Download  www.lrec-conf.org
    We introduce the corpus of United States Congressional bills from 1947 to 1998 for use by language research communities. The U.S. Policy Agenda Legislation Corpus Volume 1 (USPALC...
    Stephen Purpura, John Wilkerson, Dustin Hillard
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    OZCHI
    2006
    ACM
    107views Human Computer Interaction» more  OZCHI 2006»
    A wearable folding display for self-expression
    14 years 2 months ago
    A wearable folding display for self-expression
    Download  web.arch.usyd.edu.au
    This paper proposes the design rationale of a wearable display that is able to convey the behavioral typology of its wearers by merging insights from wearable computing, aesthetic...
    Andrew Vande Moere, Monika Hoinkis
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    ECCV
    2000
    Springer
    270views Computer Vision» more  ECCV 2000»
    Unsupervised Learning of Models for Recognition
    14 years 10 months ago
    Unsupervised Learning of Models for Recognition
    Download  www.vision.caltech.edu
    We present a method to learn object class models from unlabeled and unsegmented cluttered scenes for the purpose of visual object recognition. We focus on a particular type of mode...
    Markus Weber, Max Welling, Pietro Perona
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