activity
20192026
most citedMonte Carlo Estimation for Imprecise Probabilities: Basic Properties

6 citations · 6 across the 4 of their papers we have counts for

collaborators

5 papers

math.CO2026

On the maximum product of distances of diameter point sets

Stijn Cambie, Arne Decadt, Yanni Dong +2

We consider a problem posed by Erdős, Herzog and Piranian on the maximum product of distances of a point set of order with a given diameter. We prove that it is sufficient to c…

cs.AI2024

Extending choice assessments to choice functions: An algorithm for computing the natural extension

Arne Decadt, Alexander Erreygers, Jasper De Bock

We study how to infer new choices from prior choices using the framework of choice functions, a unifying mathematical framework for decision-making based on sets of preference orde…

cs.AI2022

Decision-making with E-admissibility given a finite assessment of choices

Arne Decadt, Alexander Erreygers, Jasper De Bock +1

Given information about which options a decision-maker definitely rejects from given finite sets of options, we study the implications for decision-making with E-admissibility. Thi…

cs.AI2020

Inference with Choice Functions Made Practical

Arne Decadt, Jasper De Bock, Gert de Cooman

We study how to infer new choices from previous choices in a conservative manner. To make such inferences, we use the theory of choice functions: a unifying mathematical framework…

math.PR2019★ 6 cited

Monte Carlo Estimation for Imprecise Probabilities: Basic Properties

Arne Decadt, Gert de Cooman, Jasper De Bock

We describe Monte Carlo methods for estimating lower envelopes of expectations of real random variables. We prove that the estimation bias is negative and that its absolute value s…