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Boosted Statistical Relational Learners

From Benchmarks to Data-Driven Medicine

  • Sriraam Natarajan
  • Kristian Kersting
  • Tushar Khot
  • Jude Shavlik

Part of the SpringerBriefs in Computer Science book series (BRIEFSCOMPUTER)

Table of contents

  1. Front Matter
    Pages i-viii
  2. Sriraam Natarajan, Kristian Kersting, Tushar Khot, Jude Shavlik
    Pages 1-3
  3. Sriraam Natarajan, Kristian Kersting, Tushar Khot, Jude Shavlik
    Pages 5-17
  4. Sriraam Natarajan, Kristian Kersting, Tushar Khot, Jude Shavlik
    Pages 19-26
  5. Sriraam Natarajan, Kristian Kersting, Tushar Khot, Jude Shavlik
    Pages 27-38
  6. Sriraam Natarajan, Kristian Kersting, Tushar Khot, Jude Shavlik
    Pages 39-48
  7. Sriraam Natarajan, Kristian Kersting, Tushar Khot, Jude Shavlik
    Pages 49-68
  8. Back Matter
    Pages 69-74

About this book

Introduction

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 world applications. The models are highly attractive due to their compactness and comprehensibility but learning their structure is computationally intensive. To combat this problem, the authors review the use of functional gradients for boosting the structure and the parameters of statistical relational models. The algorithms have been applied successfully in several SRL settings and have been adapted to several real problems from Information extraction in text to medical problems. Including both context and well-tested applications, Boosting Statistical Relational Learning from Benchmarks to Data-Driven Medicine is designed for researchers and professionals in machine learning and data mining. Computer engineers or students interested in statistics, data management, or health informatics will also find this brief a valuable resource.

Keywords

Applications of AI Ensemble methods First order probabilistic models Reasoning under uncertainty Statistical relational learning

Authors and affiliations

  • Sriraam Natarajan
    • 1
  • Kristian Kersting
    • 2
  • Tushar Khot
    • 3
  • Jude Shavlik
    • 4
  1. 1.Indiana UniversityBloomingtonUSA
  2. 2.TU Dortmund UniversityDortmundGermany
  3. 3.Indiana UniversityBloomingtonUSA
  4. 4.University of WisconsinMadisonUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-13644-8
  • Copyright Information The Author(s) 2014
  • Publisher Name Springer, Cham
  • eBook Packages Computer Science
  • Print ISBN 978-3-319-13643-1
  • Online ISBN 978-3-319-13644-8
  • Series Print ISSN 2191-5768
  • Series Online ISSN 2191-5776
  • Buy this book on publisher's site
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