Bart Jacobs - Hyper Normalisation and Conditioning for Discrete Probability Distributions

lmcs:2009 - Logical Methods in Computer Science, August 29, 2017, Volume 13, Issue 3 - https://doi.org/10.23638/LMCS-13(3:17)2017
Hyper Normalisation and Conditioning for Discrete Probability DistributionsArticle

Authors: Bart Jacobs

    Normalisation in probability theory turns a subdistribution into a proper distribution. It is a partial operation, since it is undefined for the zero subdistribution. This partiality makes it hard to reason equationally about normalisation. A novel description of normalisation is given as a mathematically well-behaved total function. The output of this `hyper' normalisation operation is a distribution of distributions. It improves reasoning about normalisation. After developing the basics of this theory of (hyper) normalisation, it is put to use in a similarly new description of conditioning, producing a distribution of conditional distributions. This is used to give a clean abstract reformulation of refinement in quantitative information flow.


    Volume: Volume 13, Issue 3
    Published on: August 29, 2017
    Accepted on: July 30, 2017
    Submitted on: August 29, 2017
    Keywords: Computer Science - Logic in Computer Science,18C10,F.1.2,I.2.3
    Funding:
      Source : OpenAIRE Graph
    • Quantum Computation, Logic, and Security; Funder: European Commission; Code: 320571

    Consultation statistics

    This page has been seen 1368 times.
    This article's PDF has been downloaded 269 times.