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Audio generation from a single sample using deep convolutional generative adversarial networks
(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 ...
Solving non-decomposable objectives using linear programming layers in general machine learning models : SVMs and deep neural networks
(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 ...