5 papers
Reinforcement Learning for Durable Algorithmic Recourse
Marina Ceccon, Alessandro Fabris, Goran RadanoviÄ +2
Algorithmic recourse seeks to provide individuals with actionable recommendations that increase their chances of receiving favorable outcomes from automated decision systems (e.g.,…
A Fairness-Oriented Multi-Objective Reinforcement Learning approach for Autonomous Intersection Management
Matteo Cederle, Marco Fabris, Gian Antonio Susto
This study introduces a novel multi-objective reinforcement learning (MORL) approach for autonomous intersection management, aiming to balance traffic efficiency and environmental…
Fairness Evolution in Continual Learning for Medical Imaging
Marina Ceccon, Davide Dalle Pezze, Alessandro Fabris +1
Deep Learning has advanced significantly in medical applications, aiding disease diagnosis in Chest X-ray images. However, expanding model capabilities with new data remains a chal…
Testing software for non-discrimination: an updated and extended audit in the Italian car insurance domain
Marco Rondina, Antonio Vetrò, Riccardo Coppola +5
Context. As software systems become more integrated into society's infrastructure, the responsibility of software professionals to ensure compliance with various non-functional req…
A Fairness-Oriented Reinforcement Learning Approach for the Operation and Control of Shared Micromobility Services
Matteo Cederle, Luca Vittorio Piron, Marina Ceccon +4
As Machine Learning grows in popularity across various fields, equity has become a key focus for the AI community. However, fairness-oriented approaches are still underexplored in…