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    Audio generation from a single sample using deep convolutional generative adversarial networks 

    Pfantz, Levi (University of Wisconsin - Whitewater, 2021-12)
    Training neural networks require sizeable datasets for meaningful output. It is difficult to acquire large datasets for many types of data. This is especially challenging for individuals and small organizations. We have ...
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    Productivity of business at the bottom of the pyramid : a neural network analysis of the solid waste informal sector in India 

    Johnson, Neil S. (University of Wisconsin - Whitewater, 2021-12)
    In developing countries, solid waste levels have continued to climb so quickly that municipalities have been unable to handle the increasing quantity of waste. Amidst the bleak setting of uncollected waste littering the ...
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    Solving non-decomposable objectives using linear programming layers in general machine learning models : SVMs and deep neural networks 

    Woerishofer, Clint (University of Wisconsin - Whitewater, 2021-05)
    Many domain specific machine learning tasks require more fine tuning with respect to nondecomposable metrics to be effective. In many applications such as medical diagnosis and fraud detection, traditional loss measures ...

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    AuthorJohnson, Neil S. (1)Pfantz, Levi (1)Woerishofer, Clint (1)Subject
    Neural networks (Computer science) (3)
    Machine learning (2)Artificial intelligence -- Biological applications. (1)Audio frequency (1)Linear programming (1)Operations research -- Data processing. (1)Ragpickers (1)... View MoreDate Issued
    2021 (3)
    Has File(s)Yes (3)

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