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Filtering by: Committee Member Naithani, Sushma Remove constraint Committee Member: Naithani, Sushma Commencement Year 2020 Remove constraint Commencement Year: 2020 Resource Type Dissertation Remove constraint Resource Type: Dissertation

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  • Learning with Limited Labeled Data in Natural Language Processing

    Creator:
    Obeidat, Rasha
    Abstract:
    The advent of deep learning models leads to a substantial improvement in a wide range of NLP tasks, achieving state-of-art performances without any hand-crafted features. However, training deep models requires a massive amount of labeled data. Labeling new data as a new task or domain emerges consumes time and efforts...
    Resource Type:
    Dissertation
    Full Text:
    . Liang Huang, Prof Stephen A Ramsey, Prof. Brett Tyler, and Prof. Sushma Naithani, for their insight

  • Comparative Transcriptomics in Stress-Induced Rice

    Creator:
    Al-Bader, Noor M.
    Abstract:
    Rice is an important crop that feeds almost half the world population. As climate change models predict floods, drought and extreme temperatures in rice production areas, the need to better understand the genetic basis of adaptation and tolerance to abiotic and biotic stresses is vital to sustain our food supply....
    Resource Type:
    Dissertation