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Research Topic : Software
Australian State/Territory : ACT
Field of Research : Optimisation
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  • Funded Activity

    Discovery Projects - Grant ID: DP0774054

    Funder
    Australian Research Council
    Funding Amount
    $263,993.00
    Summary
    Unifying Modern Approaches in Machine Learning. The proposed research will lead to better algorithms for some important machine learning problems that could lead to better tools for extracting useful knowledge from data such as in bioinformatics and sensor networks; it will strengthen an international collaboration with one of the world's top centres of machine learning research; it will contribute to an open source toolkit of machine learning algorithms which will put Australia on the map as a .... Unifying Modern Approaches in Machine Learning. The proposed research will lead to better algorithms for some important machine learning problems that could lead to better tools for extracting useful knowledge from data such as in bioinformatics and sensor networks; it will strengthen an international collaboration with one of the world's top centres of machine learning research; it will contribute to an open source toolkit of machine learning algorithms which will put Australia on the map as a provider of sophisticated machine learning software; it will provide training opportunities for several PhD students and a postdoc to work with some of the best machine learning researchers in the world.
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    Funded Activity

    Discovery Projects - Grant ID: DP0450539

    Funder
    Australian Research Council
    Funding Amount
    $243,966.00
    Summary
    Numerical Algorithms for Solving Convex Optimization Problems Arising in Systems and Control Theory. The need to optimize occurs frequently in engineering applications. Typically one has a set of constraints specifying what solutions are allowable or meet design specifications and one would like to choose from these allowable solutions one which is optimal with respect to some meaningful metric. Such optimization problems tend to be rather complicated and must be solved numerically. This project .... Numerical Algorithms for Solving Convex Optimization Problems Arising in Systems and Control Theory. The need to optimize occurs frequently in engineering applications. Typically one has a set of constraints specifying what solutions are allowable or meet design specifications and one would like to choose from these allowable solutions one which is optimal with respect to some meaningful metric. Such optimization problems tend to be rather complicated and must be solved numerically. This project is concerned with creating improved numerical algorithms for solving particular important classes of optimization problems that arise in systems and control theory.
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