09 Set 2024 - 11 Set 2024

MOX

13th Symposium on Conformal and Probabilistic Prediction with Applications

Conformal prediction (CP) is a modern machine and statistical learning method that allows to develop valid predictions under weak probabilistic assumptions. CP can be used to form set predictions, using any underlying point predictor, and for very general target variables, allowing the error levels to be controlled by the user. Therefore, CP has been widely used to develop robust forms of probabilistic prediction methodologies, and applied to many practical real life challenges. The aim of this symposium is to serve as a forum for the presentation of new and ongoing work and the exchange of ideas between researchers on any aspect of conformal and probabilistic prediction, including their application to interesting problems in any field.

Simone Vantini (General Chair); Matteo Fontana (Programme Chair); Alfredo Gimenez Zapiola, Teresa Bortolotti, Khuong An Nguyen (Organizing Chairs); Francesca Ieva (Stakeholder Relation Chair)

Politecnico di Milano

13th Symposium on Conformal and Probabilistic Prediction with Applications