no code implementations • 12 Apr 2023 • Léo Andéol, Thomas Fel, Florence De Grancey, Luca Mossina
Deploying deep learning models in real-world certified systems requires the ability to provide confidence estimates that accurately reflect their uncertainty.
no code implementations • 26 Jan 2023 • Léo Andéol, Thomas Fel, Florence De Grancey, Luca Mossina
We present an application of conformal prediction, a form of uncertainty quantification with guarantees, to the detection of railway signals.
no code implementations • 12 Jul 2019 • Andrea Lodi, Luca Mossina, Emmanuel Rachelson
Although presented through the application to the facility location problem, the approach developed here is general and explores a new perspective on the exploitation of past experience in combinatorial optimization.
no code implementations • 9 May 2019 • Luca Mossina, Emmanuel Rachelson, Daniel Delahaye
We study how Reinforcement Learning can be employed to optimally control parameters in evolutionary algorithms.
1 code implementation • 19 Jul 2017 • Luca Mossina, Emmanuel Rachelson
This article focuses on the question of learning how to automatically select a subset of items among a bigger set.