| The Effect of Homophily on Disparate Visibility of Minorities in People Recommender Systems F Fabbri, F Bonchi, L Boratto, C Castillo Proceedings of the International AAAI Conference on Web and Social Media 14 …, 2020 | 38 | 2020 |
| Rewiring What-to-Watch-Next Recommendations to Reduce Radicalization Pathways F Fabbri, Y Wang, F Bonchi, C Castillo, M Mathioudakis Proceedings of the ACM Web Conference 2022, 2719-2728, 2022 | 26 | 2022 |
| Exposure Inequality in People Recommender Systems: The Long-Term Effects F Fabbri, ML Croci, F Bonchi, C Castillo Proceedings of the International AAAI Conference on Web and Social Media 16 …, 2022 | 22 | 2022 |
| Fair and Representative Subset Selection from Data Streams Y Wang, F Fabbri, M Mathioudakis Proceedings of the Web Conference 2021, 1340-1350, 2021 | 17 | 2021 |
| Unveiling Women’s Needs and Expectations as Users of Bike Sharing Services: The H2020 DIAMOND Project A Gorrini, R Choubassi, F Messa, W Saleh, A Ababio-Donkor, MC Leva, ... Sustainability 13 (9), 5241, 2021 | 9 | 2021 |
| Assessing the interdependencies between scientific disciplinary profiles C Daraio, F Fabbri, G Gavazzi, MG Izzo, L Leuzzi, G Quaglia, G Ruocco Scientometrics 116, 1785-1803, 2018 | 8 | 2018 |
| Streaming Algorithms for Diversity Maximization with Fairness Constraints Y Wang, F Fabbri, M Mathioudakis 2022 IEEE 38th International Conference on Data Engineering (ICDE), 41-53, 2022 | 7 | 2022 |
| Comparing Equity and Effectiveness of Different Algorithms in an Application for the Room Rental Market D Solans, F Fabbri, C Calsamiglia, C Castillo, F Bonchi Proceedings of the 2021 AAAI/ACM Conference on AI, Ethics, and Society, 978-988, 2021 | 7 | 2021 |
| The Interconnected Nature of Online Harm and Moderation: Investigating the Cross-Platform Spread of Harmful Content between YouTube and Twitter VL Gatta, L Luceri, F Fabbri, E Ferrara Proceedings of the 34th ACM Conference on Hypertext and Social Media, 1-10, 2023 | 5 | 2023 |
| GNNUERS: fairness explanation in GNNs for recommendation via counterfactual reasoning G Medda, F Fabbri, M Marras, L Boratto, G Fenu ACM Transactions on Intelligent Systems and Technology, 2023 | 5 | 2023 |
| Counterfactual Graph Augmentation for Consumer Unfairness Mitigation in Recommender Systems L Boratto, F Fabbri, G Fenu, M Marras, G Medda Proceedings of the 32nd ACM International Conference on Information and …, 2023 | 4 | 2023 |
| From the beatles to billie eilish: connecting provider representativeness and exposure in session-based recommender systems A Ariza, F Fabbri, L Boratto, M Salamó European Conference on Information Retrieval, 201-208, 2021 | 4 | 2021 |
| Max-Min Diversification with Fairness Constraints: Exact and Approximation Algorithms Y Wang, M Mathioudakis, J Li, F Fabbri Proceedings of the 2023 SIAM International Conference on Data Mining (SDM …, 2023 | 3 | 2023 |
| Robustness in fairness against edge-level perturbations in gnn-based recommendation L Boratto, F Fabbri, G Fenu, M Marras, G Medda European Conference on Information Retrieval, 38-55, 2024 | 1 | 2024 |
| Personalized Audiobook Recommendations at Spotify Through Graph Neural Networks M De Nadai, F Fabbri, P Gigioli, A Wang, A Li, F Silvestri, L Kim, S Lin, ... arXiv preprint arXiv:2403.05185, 2024 | 1 | 2024 |
| Graph Learning for Exploratory Query Suggestions in an Instant Search System E Palumbo, A Damianou, A Wang, A Liu, G Fazelnia, F Fabbri, R Ferreira, ... Proceedings of the 32nd ACM International Conference on Information and …, 2023 | 1 | 2023 |
| Fair Max–Min Diversity Maximization in Streaming and Sliding-Window Models Y Wang, F Fabbri, M Mathioudakis, J Li Entropy 25 (7), 1066, 2023 | 1 | 2023 |
| Towards Graph Foundation Models for Personalization A Damianou, F Fabbri, P Gigioli, M De Nadai, A Wang, E Palumbo, ... arXiv preprint arXiv:2403.07478, 2024 | | 2024 |
| FedFNN: Faster Training Convergence Through Update Predictions in Federated Recommender Systems F Fabbri, X Liu, JR McKenzie, B Twardowski, TK Wijaya arXiv preprint arXiv:2309.08635, 2023 | | 2023 |
| Algorithmic bias in graph-based recommender systems F Fabbri Universitat Pompeu Fabra, 2022 | | 2022 |
Carlos CastilloICREA Research Professor at Universitat Pompeu FabraVerified email at icrea.cat
