Results 11 to 20 of about 203,140 (297)
Computation with imprecise probabilities [PDF]
2008 IEEE International Conference on Information Reuse and Integration, 2008 Computation with imprecise probabilities is not an academic exercise—it is a bridge to reality. In the real world, imprecision of probabilities is the norm rather than exception. In large measure, real-world probabilities are perceptions of likelihood. Perceptions are intrinsically imprecise.
Lotfi A. Zadeh
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Probabilistic satisfiability with imprecise probabilities [PDF]
International Journal of Approximate Reasoning, 2000 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Pierre Hansen +4 more
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Transitive Reasoning with Imprecise Probabilities [PDF]
, 2015 We study probabilistically informative (weak) versions of transitivity, by using suitable definitions of defaults and negated defaults, in the setting of coherence and imprecise probabilities. We represent p-consistent sequences of defaults and/or negated defaults by g-coherent imprecise probability assessments on the respective sequences of ...
Angelo Gilio +2 more
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Stable Non-standard Imprecise Probabilities [PDF]
, 2014 Stability arises as the consistency criterion in a betting interpretation for hyperreal imprecise previsions, that is imprecise previsions (and probabilities) which may take infinitesimal values. The purpose of this work is to extend the notion of stable coherence introduced in [8] to conditional hyperreal imprecise probabilities.
F. Montagna, H. Hosni
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Combining Binary Classifiers with Imprecise Probabilities [PDF]
, 2011 This paper proposes a simple framework to combine binary classifiers whose outputs are imprecise probabilities (or are transformed into some imprecise probabilities, e.g., by using confidence intervals). This combination comes down to solve linear programs describing constraints over events (here, subsets of classes).
Destercke, Sébastien, Quost, Benjamin
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Why Credences Cannot be Imprecise [PDF]
Interdisciplinary Description of Complex Systems, 2014 Beliefs formed under uncertainty come in different grades, which are called credences or degrees of belief. The most common way of measuring the strength of credences is by ascribing probabilities to them.
Borut Trpin
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A risk-based decision framework for policy analysis of societal pandemic effects
Frontiers in Public Health, 2023 IntroductionIn this article, we summarize our findings from an EU-supported project for policy analyses applied to pandemics such as Covid-19 (with the potential to be applied as well to other, similar hazards) while considering various mitigation levels
Mats Danielson +5 more
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Upgrading the Fusion of Imprecise Classifiers
Entropy, 2023 Imprecise classification is a relatively new task within Machine Learning. The difference with standard classification is that not only is one state of the variable under study determined, a set of states that do not have enough information against them ...
Serafín Moral-García +2 more
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Imprecise Credences and Acceptance
Ergo, An Open Access Journal of Philosophy, 2022 Elga (2010) argues that no plausible decision rule governs action with imprecise credences. I follow Moss (2015a) in claiming that the solution to Elga’s challenge is found in the philosophy of mind, not in devising a special new decision rule.
Benjamin Lennertz
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Forecasting with imprecise probabilities
International Journal of Approximate Reasoning, 2012 We review de Finetti’s two coherence criteria for determinate probabilities: coherence1defined in terms of previsions for a set of events that are undominated by the status quo – previsions immune to a sure-loss – and coherence2 defined in terms of forecasts for events undominated in Brier score by a rival forecast.
Teddy Seidenfeld +2 more
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