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Field of Research : Analysis Of Algorithms And Complexity
Australian State/Territory : QLD
Research Topic : Software
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Analysis Of Algorithms And Complexity (4)
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  • Funded Activity

    Discovery Projects - Grant ID: DP1094516

    Funder
    Australian Research Council
    Funding Amount
    $625,000.00
    Summary
    Algorithms and computation in four-dimensional topology. This project will establish Australia as a world leader in computational topology, particularly in the all-important areas of topology in three and four dimensions. In four dimensions this work will be truly groundbreaking; until now the field has seen little development due to the complexity of the algorithms and computations required, and the applicant is in the unique position of having the necessary tools to make significant progress .... Algorithms and computation in four-dimensional topology. This project will establish Australia as a world leader in computational topology, particularly in the all-important areas of topology in three and four dimensions. In four dimensions this work will be truly groundbreaking; until now the field has seen little development due to the complexity of the algorithms and computations required, and the applicant is in the unique position of having the necessary tools to make significant progress in a feasible time frame. In three dimensions this project will strengthen the distinguished computational topology community in Melbourne, led by pioneers such as Rubinstein, Goodman, Hodgson as well as the applicant himself.
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    Funded Activity

    Discovery Projects - Grant ID: DP0557303

    Funder
    Australian Research Council
    Funding Amount
    $205,000.00
    Summary
    Coarse Grained Parallel Algorithms. Various fields of research face barriers created by problems that are computationally hard and/or require processing of large amounts of data. For example, some computational biochemistry methods on protein or gene sequences can not be scaled up to data sets required for human health research because of performance problems. Parallel computing enables new research by increasing the size of solvable problems. In addition to fundamental parallel computing resear .... Coarse Grained Parallel Algorithms. Various fields of research face barriers created by problems that are computationally hard and/or require processing of large amounts of data. For example, some computational biochemistry methods on protein or gene sequences can not be scaled up to data sets required for human health research because of performance problems. Parallel computing enables new research by increasing the size of solvable problems. In addition to fundamental parallel computing research, this project studies parallel algorithms for structure-based drug design and protein-protein interaction prediction that will enable new biochemistry research, as well as parallel algorithms for data cubes that will help enable the next generation of very large data warehouses.
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    Funded Activity

    Discovery Projects - Grant ID: DP0773331

    Funder
    Australian Research Council
    Funding Amount
    $380,813.00
    Summary
    Efficient Pre-Processing of Hard Problems: New Approaches, Basic Theory and Applications. Computers store even larger amounts of data about all aspects of human and industrial activity. However, they have not become significantly better at solving common problems in optimization and search. Traditional complexity theory indicates many of these problems require algorithms that are very unlikely to exist. The Parameterized Complexity approach allows us to obtain very efficient algorithms for a lar .... Efficient Pre-Processing of Hard Problems: New Approaches, Basic Theory and Applications. Computers store even larger amounts of data about all aspects of human and industrial activity. However, they have not become significantly better at solving common problems in optimization and search. Traditional complexity theory indicates many of these problems require algorithms that are very unlikely to exist. The Parameterized Complexity approach allows us to obtain very efficient algorithms for a large variety of problems, but the machinery required was diverse and complicated. This research will organize the machinery into a new approach that systematically finds good algorithms by applying simplifications around a parameter of the domain of the problem. As a result, efficient algorithms are obtained for many diverse areas.
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    Funded Activity

    Discovery Projects - Grant ID: DP0209818

    Funder
    Australian Research Council
    Funding Amount
    $181,538.00
    Summary
    Approximate proximity for applications in data mining and visualization. Data Mining, pattern recognition and visualization of relational information are all important data analysis techniques in which it is essential to determine which data points are in the vicinity of others. The huge size of the data sets involved and the need for real-time interaction preclude the use of conventional methods for the precise computation of the proximity information required. This project will develop efficie .... Approximate proximity for applications in data mining and visualization. Data Mining, pattern recognition and visualization of relational information are all important data analysis techniques in which it is essential to determine which data points are in the vicinity of others. The huge size of the data sets involved and the need for real-time interaction preclude the use of conventional methods for the precise computation of the proximity information required. This project will develop efficient algorithms and data structures for gathering high-quality approximations of the full proximity information, and will use these innovations as the basis for new, practical tools for visualization, and clustering in data mining.
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    Showing 1-4 of 4 Funded Activites

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