In this work we introduce the personalized online super learner (POSL), an online
personalizable ensemble machine learning algorithm for streaming data. POSL optimizes …

This paper addresses the prediction of the total damage costs brought on by a drought
episode under the French “Régime de Catastrophes Naturelles”. Due to the specificity of this …

Estimating quantiles of an outcome conditional on covariates is of fundamental interest in
statistics with broad application in probabilistic prediction and forecasting. We propose an …

Drought events are the second most expensive type of natural disaster within the French
legal framework known as the natural disasters compensation scheme. In recent years …

This paper deals with the prediction of the total amount of the damages caused by a drought
episode under the French “Catastrophe Naturelle” regime. Due to the specificity of this …

Drought events rank as the second most costly natural disasters within the French legal
framework of the natural disaster compensation scheme. A critical aspect of the national …

Intensive longitudinal data, defined as time-varying data collected frequently over time,
holds immense promise to advance many healthcare and public health concerns. High …

Optimal transport (OT) is a powerful mathematical theory at the interface between the
theories of optimization and probability, with many applications in a wide range of fields …

Dans un contexte d'augmentation du coût des dommages assurés lié aux événements
climatiques, d'un niveau déjà élevé, les assureurs ont vocation à participer à l'amélioration …