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Weighted Probabilistic Opinion Pooling Based on Cross-Entropy

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985556%3A_____%2F15%3A00450905" target="_blank" >RIV/67985556:_____/15:00450905 - isvavai.cz</a>

  • Result on the web

    <a href="http://dx.doi.org/10.1007/978-3-319-26535-3" target="_blank" >http://dx.doi.org/10.1007/978-3-319-26535-3</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1007/978-3-319-26535-3" target="_blank" >10.1007/978-3-319-26535-3</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Weighted Probabilistic Opinion Pooling Based on Cross-Entropy

  • Original language description

    In this work we focus on opinion pooling in the finite group of sources introduced in [Seckarova, 2015]. This approach, heavily exploiting Kullback-Leibler divergence (also known as cross-entropy), allows us to combine sources? opinions given in probabilistic form, i.e. represented by the probability mass function (pmf). However, this approach assumes that sources are equally reliable with no preferences on, e.g., importance of a particular source. The discussion about the influence of the combination by preferences among sources (represented by weights) and numerical demonstration of the derived theory on an illustrative example form the core of this contribution.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

    BC - Theory and management systems

  • OECD FORD branch

Result continuities

  • Project

    <a href="/en/project/GA13-13502S" target="_blank" >GA13-13502S: Fully Probabilistic Design of Dynamic Decision Strategies for Imperfect Participants in Market Scenarios</a><br>

  • Continuities

    I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2015

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    Neural Information Processing

  • ISBN

    978-3-319-26534-6

  • ISSN

    0302-9743

  • e-ISSN

  • Number of pages

    7

  • Pages from-to

    623-629

  • Publisher name

    Springer International Publishing

  • Place of publication

    Cham

  • Event location

    Istanbul

  • Event date

    Nov 9, 2015

  • Type of event by nationality

    EUR - Evropská akce

  • UT code for WoS article