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- Untying black boxes with clustering-based symbolic knowledge extraction (article in journal, 2024) — Federico Sabbatini, Roberta Calegari
- Unmasking the Shadows: Leveraging Symbolic Knowledge Extraction to Discover Biases and Unfairness in Opaque Predictive Models (paper in proceedings, 2024) — Federico Sabbatini, Roberta Calegari
- Enforcing Fairness via Constraint Injection with FaUCI (paper in proceedings, 2024) — Matteo Magnini, Giovanni Ciatto, Roberta Calegari, Andrea Omicini
- Proceedings of the 2nd Workshop on Fairness and Bias in AI co-located with 27th European Conference on Artificial Intelligence (ECAI 2024) (edited volume, 2024) — Roberta Calegari, Virginia Dignum, Barry O'Sullivan
- Long-Term Fairness Strategies in Ranking with Continuous Sensitive Attributes (paper in proceedings, 2024) — Luca Giuliani, Eleonora Misino, Roberta Calegari, Michele Lombardi
- Hierarchical Knowledge Extraction from Opaque Machine Learning Predictors (paper in proceedings, 2024) — Federico Sabbatini, Roberta Calegari
- Ensuring Fairness Stability for Disentangling Social Inequality in Access to Education: the FAiRDAS General Method (paper in proceedings, 2024) — Eleonora Misino, Roberta Calegari, Michele Lombardi, Michela Milano
- AI-fairness and equality of opportunity: a case study on educational achievement (paper in proceedings, 2024) — Ángel S. Marrero, Gustavo A. Marrero, Carlos Bethencourt, Liam James, Roberta Calegari
- Generation of Clinical Skin Images with Pathology with Scarce Data (paper in proceedings, 2024) — Andrea Borghesi, Roberta Calegari
- Symbolic Knowledge Comparison: Metrics and Methodologies for Multi-Agent Systems (paper in proceedings, 2024) — Federico Sabbatini, Christel Sirocchi, Roberta Calegari
- ICE: An Evaluation Metric to Assess Symbolic Knowledge Quality (paper in proceedings, 2024) — Federico Sabbatini, Roberta Calegari
- Proceedings of the 1st Workshop on AI bias: Measurements, Mitigation, Explanation Strategies co-located with the AI Fairness Cluster Inaugural Conference 2024 (edited volume, 2023) — Roberta Calegari, Carlos Castillo, Symeon Papadopoulos, Roger Soraa
- Assessing and Enforcing Fairness in the AI Lifecycle (paper in proceedings, 2023) — Roberta Calegari, Gabriel G. Castañé, Michela Milano, Barry O’Sullivan
- A geometric framework for fairness (paper in proceedings, 2023) — Alessandro Maggio, Luca Giuliani, Roberta Calegari, Michele Lombardi, Michela Milano
- Unlocking Insights and Trust: The Value of Explainable Clustering Algorithms for Cognitive Agents (paper in proceedings, 2023) — Federico Sabbatini, Roberta Calegari
- FAiRDAS: Fairness-Aware Ranking as Dynamic Abstract System (paper in proceedings, 2023) — Eleonora Misino, Roberta Calegari, Michele Lombardi, Michela Milano
- ExACT Explainable Clustering: Unravelling the Intricacies of Cluster Formation (paper in proceedings, 2023) — Federico Sabbatini, Roberta Calegari
- Unveiling Opaque Predictors via Explainable Clustering: The CReEPy Algorithm (paper in proceedings, 2023) — Federico Sabbatini, Roberta Calegari
- Achieving Complete Coverage with Hypercube-Based Symbolic Knowledge-Extraction Techniques (paper in proceedings, 2023) — Federico Sabbatini, Roberta Calegari