Browse by Subject "Machine learning"

  • Ravishankar, Saiprasad (2014-12-05)
    The sparsity of signals and images in a certain transform domain or dictionary has been exploited in many applications in signal processing, image processing, and medical imaging. Analytical sparsifying transforms such as ...

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  • Lee, Soomin (2013-05-24)
    A number of important problems that arise in various application domains can be formulated as a distributed convex constrained minimization problem over a multi-agent network. The problem is usually defined as a sum of ...

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  • Varatharajah, Yogatheesan (2015-12-07)
    Seizure prediction is a problem in biomedical science which now is possible to solve with machine learning methods. A seizure prediction system has the power to assist those affected by epilepsy in better managing their ...

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  • Chang, Ming-Wei (2012-02-06)
    Structured tasks, which often involve many interdependent decisions for each example, are the backbone for many important applications such as natural language processing tasks. The models built for structured tasks need ...

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  • Chandrasekaran, Sriram (2013-08-22)
    The genotype and the environment significantly influence the behavior and phenotype of an organism. Yet the mechanism by which a simple genetic change or environmental perturbation alters the state of an organism at the ...

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