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Filtering by: Creator Herzing, Andrew A. Remove constraint Creator: Herzing, Andrew A. Committee Member Wong, Weng-Keen Remove constraint Committee Member: Wong, Weng-Keen Committee Member Coakley Jr, James A Remove constraint Committee Member: Coakley Jr, James A Degree Name Master of Science (M.S.) Remove constraint Degree Name: Master of Science (M.S.)

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  • Revisiting output coding for sequential supervised learning

    Creator:
    Hao, Guohua
    Abstract:
    Markov models are commonly used for joint inference of label sequences. Unfortunately, inference scales quadratically in the number of labels, which is problematic for training methods where inference is repeatedly preformed and is the primary computational bottleneck for large label sets. Recent work has used output coding to address this...
    Resource Type:
    Masters Thesis
    Full Text:
    converting a problem with many labels to a set of problems with binary labels. Models were independently