International audienceThis short paper discusses the contributions made to the featured section on Low Quality Data. We further refine the distinction between the ontic and epistemic views of imprecise data in statistics. We also question the extent to which likelihood functions can be viewed as belief functions. Finally we comment on the data disambiguation effect of learning methods, relating it to data reconciliation problems
In many application settings, the data have missing entries which make analysis challenging. An abun...
Jim Joyce argues for two amendments to probabilism. The first is the doctrine that credences are rat...
AbstractThis paper extends the theory of belief functions by introducing new concepts and techniques...
International audienceThis short paper discusses the contributions made to the featured section on L...
In information processing tasks, sets may have a conjunctive or a disjunctive reading. In the conjun...
Maximum likelihood is a standard approach to computing a probability distribution that best fits a g...
AbstractThis article tries to clarify some aspects of the theory of belief functions especially with...
This thesis provides an exploration of the interplay between imprecise probability and statistics. M...
International audienceThe two main uncertainty representations in the literature that tolerate impre...
There is a growing interest in the foundations as well as the application of imprecise probability i...
AbstractThis paper distinguishes between objective probability—or chance—and subjective probability....
This paper addresses the following question: how should we update our beliefs after observing some i...
International audienceSets, hence fuzzy sets, may have a conjunctive or a disjunctive reading. In th...
This paper discusses how real-life statistical analysis/inference deviates from ideal environments. ...
In our model an individual forms beliefs over events based on the frequencies of occurrences of the ...
In many application settings, the data have missing entries which make analysis challenging. An abun...
Jim Joyce argues for two amendments to probabilism. The first is the doctrine that credences are rat...
AbstractThis paper extends the theory of belief functions by introducing new concepts and techniques...
International audienceThis short paper discusses the contributions made to the featured section on L...
In information processing tasks, sets may have a conjunctive or a disjunctive reading. In the conjun...
Maximum likelihood is a standard approach to computing a probability distribution that best fits a g...
AbstractThis article tries to clarify some aspects of the theory of belief functions especially with...
This thesis provides an exploration of the interplay between imprecise probability and statistics. M...
International audienceThe two main uncertainty representations in the literature that tolerate impre...
There is a growing interest in the foundations as well as the application of imprecise probability i...
AbstractThis paper distinguishes between objective probability—or chance—and subjective probability....
This paper addresses the following question: how should we update our beliefs after observing some i...
International audienceSets, hence fuzzy sets, may have a conjunctive or a disjunctive reading. In th...
This paper discusses how real-life statistical analysis/inference deviates from ideal environments. ...
In our model an individual forms beliefs over events based on the frequencies of occurrences of the ...
In many application settings, the data have missing entries which make analysis challenging. An abun...
Jim Joyce argues for two amendments to probabilism. The first is the doctrine that credences are rat...
AbstractThis paper extends the theory of belief functions by introducing new concepts and techniques...
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