5 citations · 15 across the 12 of their papers we have counts for
12 papers
Reinforcement Learning for Durable Algorithmic Recourse
Marina Ceccon, Alessandro Fabris, Goran Radanović +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…
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…
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…
Multi-Label Continual Learning for the Medical Domain: A Novel Benchmark
Marina Ceccon, Davide Dalle Pezze, Alessandro Fabris +1
Despite the critical importance of the medical domain in Deep Learning, most of the research in this area solely focuses on training models in static environments. It is only in re…
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…
Artificial Intelligence across Europe: A Study on Awareness, Attitude and Trust
Teresa Scantamburlo, Atia Cortés, Francesca Foffano +4
This paper presents the results of an extensive study investigating the opinions on Artificial Intelligence (AI) of a sample of 4,006 European citizens from eight distinct countrie…
Algorithmic Fairness Datasets: the Story so Far
Alessandro Fabris, Stefano Messina, Gianmaria Silvello +1
Data-driven algorithms are studied in diverse domains to support critical decisions, directly impacting people's well-being. As a result, a growing community of researchers has bee…
Incentives for Item Duplication under Fair Ranking Policies
Giorgio Maria Di Nunzio, Alessandro Fabris, Gianmaria Silvello +1
Ranking is a fundamental operation in information access systems, to filter information and direct user attention towards items deemed most relevant to them. Due to position bias,…
Measuring Fairness Under Unawareness of Sensitive Attributes: A Quantification-Based Approach
Alessandro Fabris, Andrea Esuli, Alejandro Moreo +1
Algorithms and models are increasingly deployed to inform decisions about people, inevitably affecting their lives. As a consequence, those in charge of developing these models mus…
Algorithmic Audit of Italian Car Insurance: Evidence of Unfairness in Access and Pricing
Alessandro Fabris, Alan Mishler, Stefano Gottardi +4
We conduct an audit of pricing algorithms employed by companies in the Italian car insurance industry, primarily by gathering quotes through a popular comparison website. While ack…
Gender Stereotype Reinforcement: Measuring the Gender Bias Conveyed by Ranking Algorithms
Alessandro Fabris, Alberto Purpura, Gianmaria Silvello +1
Search Engines (SE) have been shown to perpetuate well-known gender stereotypes identified in psychology literature and to influence users accordingly. Similar biases were found en…