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Computing lower and upper expectations under epistemic independence

descriptionPublicationkeyboard_double_arrow_right Article , Conference object 01 Mar 2007 Netherlands, United Kingdom English Publisher:Elsevier BVJournal:International Journal of Approximate Reasoning, volume 44, pages 244-260 (issn: 0888-613X, Copyright policy )
Authors: Cassio Polpo de Campos; Fábio Gagliardi Cozman;

doi: 10.1016/j.ijar.2006.07.013

Computing lower and upper expectations under epistemic independence

Abstract

zbMATH Open Web Interface contents unavailable due to conflicting licenses.

Countries
Netherlands, United Kingdom
Related Organizations
Keywords

concepts of independence, Epistemic independence, Imprecise probabilities, Applied Mathematics, Reasoning under uncertainty in the context of artificial intelligence, 004, Multilinear programming, Theoretical Computer Science, sets of probability measures, Artificial Intelligence, Sets of probability measures, imprecise probabilities, epistemic independence, multilinear programming, Concepts of independence, Software

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    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    		 17
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    		 Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    		 Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    		 Top 10%
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
17
Average
Top 10%
Top 10%
Green
hybrid
Related to Research communities
Knowmad Institut
Netherlands Research Portal