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    ACL
    2009
    138views Computational Linguistics» more  ACL 2009»
    Semi-supervised Learning for Automatic Prosodic Event Detection Using Co-training Algorithm
    13 years 6 months ago
    Semi-supervised Learning for Automatic Prosodic Event Detection Using Co-training Algorithm
    Download  www.aclweb.org
    Most of previous approaches to automatic prosodic event detection are based on supervised learning, relying on the availability of a corpus that is annotated with the prosodic lab...
    Je Hun Jeon, Yang Liu
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    NIPS
    2007
    217views Information Technology» more  NIPS 2007»
    Semi-Supervised Multitask Learning
    13 years 10 months ago
    Semi-Supervised Multitask Learning
    Download  books.nips.cc
    A semi-supervised multitask learning (MTL) framework is presented, in which M parameterized semi-supervised classifiers, each associated with one of M partially labeled data mani...
    Qiuhua Liu, Xuejun Liao, Lawrence Carin
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    ICMLA
    2007
    192views Machine Learning» more  ICMLA 2007»
    Semi-Supervised Active Learning for Modeling Medical Concepts from Free Text
    13 years 10 months ago
    Semi-Supervised Active Learning for Modeling Medical Concepts from Free Text
    Download  people.csail.mit.edu
    We apply a new active learning formulation to the problem of learning medical concepts from unstructured text. The new formulation is based on maximizing the mutual information th...
    Rómer Rosales, Praveen Krishnamurthy, R. Bh...
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    ICWSM
    2009
    189views Internet Technology» more  ICWSM 2009»
    Targeting Sentiment Expressions through Supervised Ranking of Linguistic Configurations
    13 years 6 months ago
    Targeting Sentiment Expressions through Supervised Ranking of Linguistic Configurations
    Download  www.cs.indiana.edu
    User generated content is extremely valuable for mining market intelligence because it is unsolicited. We study the problem of analyzing users' sentiment and opinion in their...
    Jason S. Kessler, Nicolas Nicolov
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    ECML
    2006
    Springer
    221views Machine Learning» more  ECML 2006»
    Unsupervised Multiple-Instance Learning for Functional Profiling of Genomic Data
    14 years 21 days ago
    Unsupervised Multiple-Instance Learning for Functional Profiling of Genomic Data
    Download  sci2s.ugr.es
    Multiple-instance learning (MIL) is a popular concept among the AI community to support supervised learning applications in situations where only incomplete knowledge is available....
    Corneliu Henegar, Karine Clément, Jean-Dani...
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