Search Results - "DESTERCKE, S"

Comments on “Learning from imprecise and fuzzy observations: Data disambiguation through generalized loss minimization” by Eyke Hüllermeier by Destercke, S.

“…Eyke Hüllermeier provides a very convincing approach to learn from fuzzy data, both about the model and about the data themselves. In the process, he links the…”
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Comments on “A distance-based statistical analysis of fuzzy number-valued data” by the SMIRE research group by Destercke, S.

“…This paper is a fine review of various aspects related to the statistical handling of “ontic” random fuzzy sets by the means of appropriate distances. It is…”
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Idempotent conjunctive combination of belief functions: Extending the minimum rule of possibility theory by Destercke, S., Dubois, D.

“…When conjunctively merging two belief functions concerning a single variable but coming from different sources, Dempster rule of combination is justified only…”
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Toward an Axiomatic Definition of Conflict Between Belief Functions by Destercke, S., Burger, T.

“…Recently, the problem of measuring the conflict between two bodies of evidence represented by belief functions has known a regain of interest. In most works…”
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Unifying parameter learning and modelling complex systems with epistemic uncertainty using probability interval by Baudrit, C., Destercke, S., Wuillemin, P.H.

“…•Knowledge regarding complex systems are heterogeneous and fragmented.•modelling dynamic complex systems in the framework of dynamic credal networks.•practical…”
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Easy and optimal queries to reduce set uncertainty by Ben Abdallah, N., Destercke, S., Sallak, M.

“…•A setting for optimal expert elicitation to reduce set uncertainty is described.•The formal approach is justified by simulated experiments in reliability.•The…”
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Parameter uncertainties and error propagation in modified atmosphere packaging modelling by Guillard, V., Guillaume, C., Destercke, S.

“…► Interval analysis is proposed to study error propagation in MAP modelling for 3 fresh produce. ► Results are compared to a probabilistic Monte–Carlo…”
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Possibilistic Information Fusion Using Maximal Coherent Subsets by Destercke, S., Dubois, D., Chojnacki, E.

“…When multiple sources provide information about the same unknown quantity, their fusion into a synthetic interpretable message is often a tricky problem,…”
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Inclusion–exclusion principle for belief functions by Aguirre, F., Destercke, S., Dubois, D., Sallak, M., Jacob, C.

“…The inclusion–exclusion principle is a well-known property in probability theory, and is instrumental in some computational problems such as the evaluation of…”
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Unifying practical uncertainty representations. II: Clouds by Destercke, S., Dubois, D., Chojnacki, E.

“…There exist many simple tools for jointly capturing variability and incomplete information by means of uncertainty representations. Among them are random sets,…”
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Methods for the evaluation and synthesis of multiple sources of information applied to nuclear computer codes by Destercke, S., Chojnacki, E.

“…This work is devoted to methods used to evaluate and synthesize information given by multiple sources about a variable which true value is not precisely known…”
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Independence and 2-monotonicity: Nice to have, hard to keep: Eleventh European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty (ECSQARU 2011) by DESTERCKE, S

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An extension of Universal Generating Function in Multi-State Systems Considering Epistemic Uncertainties by Destercke, S., Sallak, M.

“…Many practical methods and different approaches have been proposed to assess Multi-State Systems (MSS) reliability measures. The universal generating function…”
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Independence and 2-monotonicity: Nice to have, hard to keep by Destercke, S.

“…► We show that classical independence model do not preserve 2-monotonicity. ► We propose an outer-approximating 2-monotone joint model based on the Mobius…”
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Evaluating Data Reliability: An Evidential Answer with Application to a Web-Enabled Data Warehouse by Destercke, S., Buche, P., Charnomordic, B.

“…There are many available methods to integrate information source reliability in an uncertainty representation, but there are only a few works focusing on the…”
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Unifying practical uncertainty representations – I: Generalized p-boxes by Destercke, S., Dubois, D., Chojnacki, E.

“…There exist several simple representations of uncertainty that are easier to handle than more general ones. Among them are random sets, possibility…”
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Computing Expectations with Continuous P-Boxes: Univariate Case by Utkin, L, Destercke, S

“…International Journal of Approximate Reasoning, Vol 50, n 5, pp 778-798, 2009 Given an imprecise probabilistic model over a continuous space, computing…”
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Uncertainty, elicitation of experts' opinion, and human failures: Challenges for RAM analysis of ERTMS SoS by Sallak, M., Destercke, S., Schon, W., Vanderhaegen, F., Berdjag, D., Simon, C.

“…This paper has three main objectives. The first objective is to summarize the requirements for RAM (Reliability, Availability, and Maintainability) parameters…”
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Possibilistic information fusion using maximal coherent subsets by Destercke, S., Dubois, D., Chojnacki, E.

“…When multiple sources provide information about the same unknown quantity, their fusion into a synthetic interpretable message is often a tedious problem,…”
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Using the OLS algorithm to build interpretable rule bases: an application to a depollution problem by Destercke, S., Guillaume, S., Charnomordic, B.

“…One of the main advantages of fuzzy modeling is the ability to yield interpretable results. Amongst these modeling methods, the OLS algorithm is a…”
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