Maximum Entropy Beyond Selecting Probability Distributions

  • Thach N. Nguyen
  • Olga Kosheleva
  • Vladik Kreinovich
Conference paper
Part of the Studies in Computational Intelligence book series (SCI, volume 760)

Abstract

Traditionally, the Maximum Entropy technique is used to select a probability distribution in situations when several different probability distributions are consistent with our knowledge. In this paper, we show that this technique can be extended beyond selecting probability distributions, to explain facts, numerical values, and even types of functional dependence.

Notes

Acknowledgments

This work was supported in part by the National Science Foundation grant HRD-1242122 (Cyber-ShARE Center of Excellence).

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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • Thach N. Nguyen
    • 1
  • Olga Kosheleva
    • 2
  • Vladik Kreinovich
    • 2
  1. 1.Banking University of Ho Chi Minh CityHo Chi Minh CityVietnam
  2. 2.University of Texas at El PasoEl PasoUSA

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