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On Probabilistic Conditional Independence Structures pp 111–129Cite as

Equivalence and Implication

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Part of the Information Science and Statistics book series (ISS)

Keywords

  • Probability Measure
  • Discrete Measure
  • Chain Graph
  • Markovian Measure
  • Supermodular Function

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Editor information

Editors and Affiliations

  1. Division of Computer Science and Department of Statistics, University of California, Berkeley, Berkeley, CA, 94720, USA

    Michael Jordan

  2. Department of Computer Science, Cornell University, Ithaca, NY, 14853, USA

    Jon Kleinberg

  3. Max Planck Institute for Biological Cybernetics, Spemannstrasse 38, 72076, Tübingen, Germany

    Bernhard Schölkopf

  4. Statistical Laboratory, Centre for Mathematical Sciences, Wilberforce Road, Cambridge, CB3 0WB, UK

    Frank P. Kelly

  5. Department of Computer Science, University of Waikato, Hamilton, New Zealand

    Ian Witten

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© 2005 Springer-Verlag London Limited

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(2005). Equivalence and Implication. In: Jordan, M., Kleinberg, J., Schölkopf, B., Kelly, F.P., Witten, I. (eds) On Probabilistic Conditional Independence Structures. Information Science and Statistics. Springer, London. https://doi.org/10.1007/1-84628-083-4_6

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  • DOI: https://doi.org/10.1007/1-84628-083-4_6

  • Publisher Name: Springer, London

  • Print ISBN: 978-1-85233-891-6

  • Online ISBN: 978-1-84628-083-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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