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Research Topic : Machine learning algorithms
Australian State/Territory : VIC
Field of Research : Data Format
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Data Format (5)
Analysis of Algorithms and Complexity (3)
Data Structures (3)
Analysis Of Algorithms And Complexity (1)
Coding And Information Theory (1)
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  • Funded Activity

    Discovery Projects - Grant ID: DP0345189

    Funder
    Australian Research Council
    Funding Amount
    $587,275.00
    Summary
    Stochastic Construction of Error Correcting Codes with Application to Digital Communications. Modern society would be unrecognisable without error correcting codes; mobile telephones, storage devices such as DVD's and high speed data communications simply would not exist. Yet most theoretical results on error correcting codes are asymptotic in nature and ignore computational complexity issues, that is, they are not representative of many real life situations. By building on recent breakthrough .... Stochastic Construction of Error Correcting Codes with Application to Digital Communications. Modern society would be unrecognisable without error correcting codes; mobile telephones, storage devices such as DVD's and high speed data communications simply would not exist. Yet most theoretical results on error correcting codes are asymptotic in nature and ignore computational complexity issues, that is, they are not representative of many real life situations. By building on recent breakthroughs in statistics and stochastic optimisation, this project will develop algorithms for designing optimised error correcting codes subject to realistic finite data length and computational complexity constraints. Successful outcomes will lead to enhanced data communications and storage, greatly benefiting industry and consumers alike.
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    Funded Activity

    Discovery Projects - Grant ID: DP140103256

    Funder
    Australian Research Council
    Funding Amount
    $310,000.00
    Summary
    Data retrieval from massive information structures. Information search is an essential tool. But most current services regard the data as unstructured collections of independent documents, free of context. Next-generation search applications, such as over social networks, or corporate websites, or XML data sets, must account for the inherent relationships between data items, and must allow the efficient inclusion of search context. Queries should favour semantically local data, giving results th .... Data retrieval from massive information structures. Information search is an essential tool. But most current services regard the data as unstructured collections of independent documents, free of context. Next-generation search applications, such as over social networks, or corporate websites, or XML data sets, must account for the inherent relationships between data items, and must allow the efficient inclusion of search context. Queries should favour semantically local data, giving results that depend on the perceived state of the querier. This project will develop indexing and search techniques for massive structured data sets. The new search methods will incorporate theoretical advances and will be experimentally validated using industry-standard open-source distributed systems.
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    Funded Activity

    Discovery Projects - Grant ID: DP110101743

    Funder
    Australian Research Council
    Funding Amount
    $360,000.00
    Summary
    Efficient and effective algorithms for searching strings in secondary storage. Pattern searching is fundamental to a wide range of computing applications, including web search and bioinformatics. In this project we will develop compression algorithms and hybrid memory-disk search structures that allow fast pattern matching on sequences of textual and numeric data, including when approximate search is required.
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    Funded Activity

    Discovery Projects - Grant ID: DP0771504

    Funder
    Australian Research Council
    Funding Amount
    $246,090.00
    Summary
    Efficient Algorithms for In-memory Sorting, Searching and Indexing on Modern Multi-core Cache-based and Graphics Processor Architectures. This project clearly belongs to one of the national research priority goals, Smart Information Use. The copy-based techniques and work on sorting and searching will considerably impact the development of in-memory algorithms in cutting-edge computer architectures. Efficient suffix trees and suffix sorting have myriad applications in string-processing and will .... Efficient Algorithms for In-memory Sorting, Searching and Indexing on Modern Multi-core Cache-based and Graphics Processor Architectures. This project clearly belongs to one of the national research priority goals, Smart Information Use. The copy-based techniques and work on sorting and searching will considerably impact the development of in-memory algorithms in cutting-edge computer architectures. Efficient suffix trees and suffix sorting have myriad applications in string-processing and will be of high interest to bioinformatics companies. The sortdex project will develop novel algorithms that will be used by enterprise search engine companies to develop applications for libraries and organisations dealing with large databases. Algorithms using the graphics processor as a co-processor have important applications in the high-growth field of computer graphics and games.
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    Funded Activity

    Discovery Projects - Grant ID: DP150100285

    Funder
    Australian Research Council
    Funding Amount
    $262,200.00
    Summary
    New Efficient Cryptographic Tools for Data Privacy and Software Protection. Online services for collaborative communication and software distribution are commonplace today, but their use is hampered by data privacy breaches and intellectual property violations via software reverse engineering. Recent theoretical breakthroughs in cryptography promise to provide new powerful tools for solving these problems, but these tools are not yet suitable for practical use, due to their low efficiency and a .... New Efficient Cryptographic Tools for Data Privacy and Software Protection. Online services for collaborative communication and software distribution are commonplace today, but their use is hampered by data privacy breaches and intellectual property violations via software reverse engineering. Recent theoretical breakthroughs in cryptography promise to provide new powerful tools for solving these problems, but these tools are not yet suitable for practical use, due to their low efficiency and a lack of solid security foundations. This project aims to apply algebraic and probabilistic techniques to improve efficiency of existing tools, and the understanding of their security. Outcomes are expected to include new insights in cryptographic theory, and new practical tools for cyber security.
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