Numerical Sensitivity and Efficiency in the Treatment of Epistemic and Aleatory Uncertainty

The treatment of both aleatory and epistemic uncertainty by recent methods often requires an high computational effort. In this abstract, we propose a numerical sampling method allowing to lighten the computational burden of treating the information by means of so-called fuzzy random variables

Unifying Practical Uncertainty Representations: II. Clouds

There exist many simple tools for jointly capturing variability and incomplete information by means of uncertainty representations. Among them are random sets, possibility distributions, probability intervals, and the more recent Ferson's p-boxes and Neumaier's clouds, both defined by pairs of possibility distributions. In the companion paper, we have extensively studied a generalized form of p-box and situated it with respect to other models . This paper focuses on the links between clouds and other representations. Generalized p-boxes are shown to be clouds with comonotonic distributions. In general, clouds cannot always be represented by random sets, in fact not even by 2-monotone (convex) capacities.Comment: 30 pages, 7 figures, Pre-print of journal paper to be published in International Journal of Approximate Reasoning (with expanded section concerning clouds and probability intervals

ActiveRemediation: The Search for Lead Pipes in Flint, Michigan

We detail our ongoing work in Flint, Michigan to detect pipes made of lead and other hazardous metals. After elevated levels of lead were detected in residents' drinking water, followed by an increase in blood lead levels in area children, the state and federal governments directed over $125 million to replace water service lines, the pipes connecting each home to the water system. In the absence of accurate records, and with the high cost of determining buried pipe materials, we put forth a number of predictive and procedural tools to aid in the search and removal of lead infrastructure. Alongside these statistical and machine learning approaches, we describe our interactions with government officials in recommending homes for both inspection and replacement, with a focus on the statistical model that adapts to incoming information. Finally, in light of discussions about increased spending on infrastructure development by the federal government, we explore how our approach generalizes beyond Flint to other municipalities nationwide.Comment: 10 pages, 10 figures, To appear in KDD 2018, For associated promotional video, see https://www.youtube.com/watch?v=YbIn_axYu9

Aggregation of expert opinions and uncertainty theories

National audienceThe problem of expert opinions representation and aggregation has long been adressed in the only framework of probability theory. Nevertheless, recent years have witnessed many proposals in other uncertainty theories (possibility theory, evidence theory, imprecise probabilities). This paper casts the problem of aggregating expert opinions in a common underlying framework and shows how uncertainty theories fit into this framework. Differences between theories are then emphasized and discussed

Possibilistic information fusion using maximal coherent subsets (LFA 2007)

National audienceWhen multiple sources provide information about the same badly known quantity, aggregating them into a coherent and interpretable synthesis is often a tedious problem, especially when some conflict is present. In this paper, we propose and explore a fusion method using the notion of maximal coherent subsets (often used in logic) on quantitative possibility distributions. This methods result, a fuzzy belief structure, is then used to extract useful information about sources or to build a final synthetic possibility distribution.Lorsque plusieurs sources fournissent de l'information à propos d'une même quantité mal connue, en faire une synthèse cohérente et interprétable est souvent un problème difficile, surtout en présence de conflit entre les sources. Dans cet article, nous proposons et étudions une méthode de fusion basée sur la théorie des possibilités et sur la notion de sous-ensembles maximaux cohérents, une notion souvent utilisée dans le raisonnement logique. Cette méthode, dont le résultat final est une fonction de croyance floue, est ensuite utilisée aussi bien pour extraire de l'information utile sur les sources que pour construire une distribution synthétique finale

Relating Imprecise Representations of imprecise Probabilities

International audienceThere exist many practical representations of probability families that make them easier to handle. Among them are random sets, possibility distributions, probability intervals, Ferson's p-boxes and Neumaier's clouds. Both for theoretical and practical considerations, it is important to know whether one representation has the same expressive power than other ones, or can be approximated by other ones. In this paper, we mainly study the relationships between the two latter representations and the three other ones

On the relationships between random sets, possibility distributions, p-boxes and clouds

There are many practical representations of probability families that make them easier to handle in applications. Among them are random sets, possibility distributions, Ferson's p-boxes and Neumaier's clouds. Both for theoretical and practical considerations, it is very useful to know whether one representation can be translated into or approximated by other ones. We first briefly recall formalisms and existing results, before exhibiting relationships between all these representations. In this note, which is a summary of an extended forthcoming paper, we restrict ourselves to representations on a finite set X

A Data Science Approach to Understanding Residential Water Contamination in Flint

When the residents of Flint learned that lead had contaminated their water system, the local government made water-testing kits available to them free of charge. The city government published the results of these tests, creating a valuable dataset that is key to understanding the causes and extent of the lead contamination event in Flint. This is the nation's largest dataset on lead in a municipal water system. In this paper, we predict the lead contamination for each household's water supply, and we study several related aspects of Flint's water troubles, many of which generalize well beyond this one city. For example, we show that elevated lead risks can be (weakly) predicted from observable home attributes. Then we explore the factors associated with elevated lead. These risk assessments were developed in part via a crowd sourced prediction challenge at the University of Michigan. To inform Flint residents of these assessments, they have been incorporated into a web and mobile application funded by \texttt{Google.org}. We also explore questions of self-selection in the residential testing program, examining which factors are linked to when and how frequently residents voluntarily sample their water.Comment: Applied Data Science track paper at KDD 2017. For associated promotional video, see https://www.youtube.com/watch?v=0g66ImaV8A

Production of He-4 and (4) in Pb-Pb collisions at root(NN)-N-S=2.76 TeV at the LHC

Results on the production of He-4 and (4) nuclei in Pb-Pb collisions at root(NN)-N-S = 2.76 TeV in the rapidity range vertical bar y vertical bar <1, using the ALICE detector, are presented in this paper. The rapidity densities corresponding to 0-10% central events are found to be dN/dy4(He) = (0.8 +/- 0.4 (stat) +/- 0.3 (syst)) x 10(-6) and dN/dy4 = (1.1 +/- 0.4 (stat) +/- 0.2 (syst)) x 10(-6), respectively. This is in agreement with the statistical thermal model expectation assuming the same chemical freeze-out temperature (T-chem = 156 MeV) as for light hadrons. The measured ratio of (4)/He-4 is 1.4 +/- 0.8 (stat) +/- 0.5 (syst). (C) 2018 Published by Elsevier B.V.Peer reviewe