5 papers
Scenario theory for multi-criteria data-driven decision making
Simone Garatti, Lucrezia Manieri, Alessandro Falsone +3
The scenario approach provides a powerful data-driven framework for designing solutions under uncertainty with rigorous probabilistic robustness guarantees. Existing theory, howeve…
Scenario Approach with Post-Design Certification of User-Specified Properties
Algo Carè, Marco C. Campi, Simone Garatti
The scenario approach is an established data-driven design framework that comes equipped with a powerful theory linking design complexity to generalization properties. In this appr…
A Scenario-Based Approach for Stochastic Economic Model Predictive Control with an Expected Shortfall Constraint
Alireza Arastou, Algo Carè, Ye Wang +2
This paper presents a novel approach to stochastic economic model predictive control (SEMPC) that minimizes average economic cost while satisfying an empirical expected shortfall (…
Stochastic Approximation in a Markovian Framework Revisited: Lipschitz Continuity of the Poisson Equation
Algo Carè, Balázs Csanád Csáji, Balázs Gerencsér +2
In this paper we revisit a fundamental technical issue within the theory of stochastic approximation (SA) in a Markovian framework, first proposed in the book by Djereveckii and Fr…
Risk Analysis and Design Against Adversarial Actions
Marco C. Campi, Algo Carè, Luis G. Crespo +2
Learning models capable of providing reliable predictions in the face of adversarial actions has become a central focus of the machine learning community in recent years. This chal…