Per anno
- Proceedings of the 2nd Workshop on Fairness and Bias in AI co-located with 27th European Conference on Artificial Intelligence (ECAI 2024) (curatela) — Roberta Calegari, Virginia Dignum, Barry O'Sullivan
- Fairness and Bias in AI (Journal of Artificial Intelligence Research) — Roberta Calegari, Andrea Aler Tubella, Virginia Dignum, Michela Milano
- Perspectives and Challenges of Telemedicine and Artificial Intelligence in Pediatric Dermatology (Children) — Daniele Zama, Andrea Borghesi, Alice Ranieri, Elisa Manieri, Luca Pierantoni, Laura Andreozzi, Arianna Dondi, Iria Neri, Marcello Lanari, Roberta Calegari
- Bridging machine learning and diagnostics of the ESA LISA space mission with equation discovery via explainable artificial intelligence (Advances in Space Research) — Federico Sabbatini, Catia Grimani, Roberta Calegari
- Generation of Clinical Skin Images with Pathology with Scarce Data (AAAI-24) — Andrea Borghesi, Roberta Calegari
- Untying black boxes with clustering-based symbolic knowledge extraction (Intelligenza Artificiale) — Federico Sabbatini, Roberta Calegari
- Ensuring Fairness Stability for Disentangling Social Inequality in Access to Education: the FAiRDAS General Method (IJCAI 2024) — Eleonora Misino, Roberta Calegari, Michele Lombardi, Michela Milano
- Unmasking the Shadows: Leveraging Symbolic Knowledge Extraction to Discover Biases and Unfairness in Opaque Predictive Models (AEQUITAS 2024) — Federico Sabbatini, Roberta Calegari
- Enforcing Fairness via Constraint Injection with FaUCI (AEQUITAS 2024) — Matteo Magnini, Giovanni Ciatto, Roberta Calegari, Andrea Omicini
- On the Evaluation of the Symbolic Knowledge Extracted from Black Boxes (AI and Ethics) — Federico Sabbatini, Roberta Calegari
- Special Issue on Trustworthy AI (ACM Computing Surveys) — Roberta Calegari, Fosca Giannotti, Francesca Pratesi, Michela Milano
- Long-Term Fairness Strategies in Ranking with Continuous Sensitive Attributes (AEQUITAS 2024) — Luca Giuliani, Eleonora Misino, Roberta Calegari, Michele Lombardi
- Symbolic Knowledge Comparison: Metrics and Methodologies for Multi-Agent Systems (WOA 2024) — Federico Sabbatini, Christel Sirocchi, Roberta Calegari
- AI-fairness and equality of opportunity: a case study on educational achievement (AEQUITAS 2024) — Ángel S. Marrero, Gustavo A. Marrero, Carlos Bethencourt, Liam James, Roberta Calegari
0000-0003-3794-2942— Prodotti
2P
LPaaS
Arg-tuProlog
— Eventi
WOA 2021
— Progetti
CompuLaw
— Associazioni
AIxIA
— Corsi
Foundations of Informatics T-2
Multi-agent Systems (module 2)
Sem. Coding for Lawyers