A key aspect of human intelligence is their ability to convey their knowledge to others in
succinct forms. However, despite their predictive power, current machine learning models …

We study rare-event simulation for a class of problems where the target hitting sets of
interest are defined via modern machine learning tools such as neural networks and random …

Predictions of bed census are crucial for hospital capacity management choices,
encompassing ward sizing, staffing, patient bed assignments, and surgical scheduling …

Recent work in healthcare operations provide empirical evidence for the deterioration of
service quality due to congestion. Motivated by these findings, we formulate a novel …

We study a control problem for queueing systems in which customers may return for
additional episodes of service after their initial service completion. At each service …

Motivated by demand prediction for the custodial prison population in England and Wales,
this paper describes an approach to the study of service systems using infinite server …

In this study, we present an interpretable model, disjunctive rule list (DisRL) for regression.
This research is motivated by the increasing need for model interpretability, especially in …

Le phénotypage numérique mobilise les nombreux capteurs du téléphone intelligent (p. ex.:
accéléromètre, GPS, Bluetooth, métadonnées d'appels) pour mesurer le comportement …

Stochastic simulation has been widely applied in many domains. More recently, however,
the rapid surge of sophisticated problems such as safety evaluation of intelligent systems …