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    New insights on the power of active learning 

    Berlind, Christopher (Georgia Institute of Technology, 2015-07-22)
    Traditional supervised machine learning algorithms are expected to have access to a large corpus of labeled examples, but the massive amount of data available in the modern world has made unlabeled data much easier to ...

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    AuthorBerlind, Christopher (1)SubjectActive learning (1)Domain adaptation (1)Large margin learning (1)Learning theory (1)
    Machine learning (1)
    Semi-supervised learning (1)... View MoreDate Issued2015 (1)Has File(s)Yes (1)
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