Communities in DSpace

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  • DANDEKAR, Ashish; BASU, Debabrota; BRESSAN, Stephane
    Machine learning algorithms create models from training data for the purpose of estimation, prediction and classi cation. While releasing parametric machine learning models requires the release of the parameters of the ...
  • DANDEKAR, Ashish; BASU, Debabrota; BRESSAN, Stephane
    Recent attacks on machine learning models such as membership inference attacks increase the concern for privacy. Linear regression is such an essential statistical machine learning model at risk. For a given dataset, linear ...
  • DANDEKAR, Ashish; ZEN, Remmy A. M.; BRESSAN, Stephane
    Unrestricted availability of the datasets is important for the researchers to evaluate their strategies to solve the research problems. While publicly releasing the datasets, it is equally important to protect the privacy ...
  • GAO, Qiao; LEE, Mong Li; DOBBIE, Gillian; ZHONG, Zeng
    Many real world applications need to capture a mix of temporal and non-temporal entities, relationships and attributes. These concepts add complexity when designing database schemas and existing works are unable to capture ...
  • GAO, Qiao; LEE, Mong Li; LING, Tok Wang; DOBBIE, Gillian; ZENG, Zhong
    Querying temporal relational databases is a challenge for non-expert database users, since it requires users to understand the semantics of the database and apply temporal joins as well as temporal conditions correctly in ...

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