Boosted Statistical Relational Learners

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This SpringerBrief addresses the challenges of analyzing multi-relational and noisy data by proposing several Statistical Relational Learning (SRL) methods. These methods combine the expressiveness of first-order logic and the ability of probability theory to handle uncertainty. It provides an overview of the methods and the key assumptions that allow for adaptation to different models and real wo...
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This SpringerBrief addresses the challenges of analyzing multi-relational and noisy data by proposing several Statistical Relational Learning (SRL) methods. These methods combine the expressiveness of first-order logic and the ability of probability theory to handle uncertainty. It provides an overview of the methods and the key assumptions that allow for adaptation to different models and real wo...
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  • Formats: pdf
  • ISBN: 9783319136448
  • Publication Date: 3 Mar 2015
  • Publisher: Springer International Publishing
  • Product language: English
  • Drm Setting: DRM