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2023
A. Pugnana and Ruggieri, S., “AUC-based Selective Classification”, in International Conference on Artificial Intelligence and Statistics, 25-27 April 2023, Palau de Congressos, Valencia, Spain, 2023.
A. Pugnana and Ruggieri, S., “A Model-Agnostic Heuristics for Selective Classification”, in Thirty-Seventh AAAI Conference on Artificial Intelligence, AAAI 2023, 2023, Washington, DC, USA, February 7-14, 2023, 2023.
A. Pugnana, “Topics in Selective Classification”, in Thirty-Seventh AAAI Conference on Artificial Intelligence, AAAI 2023, 2023.
2022
P. Resce, Vorwerk, L., Han, Z., Cornacchia, G., Alamdari, O. Isfahani, Nanni, M., Pappalardo, L., Weimer, D., and Liu, Y., “Connected Vehicle Simulation Framework for Parking Occupancy Prediction (Demo Paper)”, in Proceedings of the 30th International Conference on Advances in Geographic Information Systems, New York, NY, USA, 2022.
F. Bodria, “Explaining Black Box with visual exploration of Latent Space”, in EuroVis, 2022.
V. Pansanella, Rossetti, G., and Milli, L., “From Mean-Field to Complex Topologies: Network Effects on the Algorithmic Bias Model”, in Complex Networks & Their Applications X, 2022.
D. Fadda, Natilli, M., and Rinzivillo, S., “GET-Viz: a library for automatic generation of visual dashboard for geographical time series”, 8th International Conference on Computational Social Science (IC2S2). Chicago, USA, 2022.
G. Cornacchia, Böhm, M., Mauro, G., Nanni, M., Pedreschi, D., and Pappalardo, L., “How Routing Strategies Impact Urban Emissions”, in Proceedings of the 30th International Conference on Advances in Geographic Information Systems, New York, NY, USA, 2022.
M. Natilli, Rossi, A., Trecroci, A., Cavaggioni, L., Merati, G., and Formenti, D., “The long-tail effect of the COVID-19 lockdown on Italians’ quality of life, sleep and physical activity”, Scientific Data, vol. 9, pp. 1–10, 2022.
A. Rita Nogueira, Pugnana, A., Ruggieri, S., Pedreschi, D., and Gama, J., “Methods and tools for causal discovery and causal inference”, WIREs Data Mining Knowl. Discov., vol. 12, 2022.
L. Corbucci, Monreale, A., Panigutti, C., Natilli, M., Smiraglio, S., and Pedreschi, D., “Semantic Enrichment of XAI Explanations for Healthcare”, 24th International Conference on Artificial Intelligence. 2022.
R. Trasarti, Grossi, V., Natilli, M., and Rapisarda, B., “SoBigData++: European Integrated Infrastructure for Social Mining and Big Data Analytics.”, 30th Italian Symposium on Advanced Database Systems (SEBD – Sistemi Evoluti per Basi di Dati). Tirrenia, Pisa, 2022.
2021
F. Bodria, Giannotti, F., Guidotti, R., Naretto, F., Pedreschi, D., and Rinzivillo, S., “Benchmarking and Survey of Explanation Methods for Black Box Models”, CoRR, vol. abs/2102.13076, 2021.
S. Marina Joseph, Citraro, S., Morini, V., Rossetti, G., and Stella, M., “Cognitive network science quantifies feelings expressed in suicide letters and Reddit mental health communities”, arXiv preprint arXiv:2110.15269, 2021.
G. Rossetti, Citraro, S., and Milli, L., “Conformity: a Path-Aware Homophily measure for Node-Attributed Networks”, IEEE Intelligent SystemsIEEE Intelligent Systems, pp. 1 - 1, 2021.
F. Lillo and Ruggieri, S., “Estimating the Total Volume of Queries to a Search Engine”, IEEE Transactions on Knowledge and Data Engineering, pp. 1-1, 2021.
L. Pappalardo, Rossi, A., Natilli, M., and Cintia, P., “Explaining the difference between men’s and women’s football”, PLOS ONE, vol. 16, p. e0255407, 2021.
M. Nanni, Andrienko, G., Barabasi, A. - L., Boldrini, C., Bonchi, F., Cattuto, C., Chiaromonte, F., Comandé, G., Conti, M., Coté, M., Dignum, F., Dignum, V., Domingo-Ferrer, J., Ferragina, P., Giannotti, F., Guidotti, R., Helbing, D., Kaski, K., Kertész, J., Lehmann, S., Lepri, B., Lukowicz, P., Matwin, S., Jiménez, D. Megías, Monreale, A., Morik, K., Oliver, N., Passarella, A., Passerini, A., Pedreschi, D., Pentland, A., Pianesi, F., Pratesi, F., Rinzivillo, S., Ruggieri, S., Siebes, A., Torra, V., Trasarti, R., van den Hoven, J., and Vespignani, A., “Give more data, awareness and control to individual citizens, and they will help COVID-19 containment”, 2021.
M. Setzu, Guidotti, R., Monreale, A., Turini, F., Pedreschi, D., and Giannotti, F., “GLocalX - From Local to Global Explanations of Black Box AI Models”, vol. 294, p. 103457, 2021.
L. Pappalardo, Grossi, V., and Pedreschi, D., “Introduction to the special issue on social mining and big data ecosystem for open, responsible data science”, 2021.
G. Cornacchia and Pappalardo, L., “A Mechanistic Data-Driven Approach to Synthesize Human Mobility Considering the Spatial, Temporal, and Social Dimensions Together”, ISPRS International Journal of Geo-Information, vol. 10, p. 599, 2021.
M. Fontana, Naretto, F., and Monreale, A., “A new approach for cross-silo federated learning and its privacy risks”, in 18th International Conference on Privacy, Security and Trust, PST 2021, Auckland, New Zealand, December 13-15, 2021, 2021.
G. Mariani, Monreale, A., and Naretto, F., “Privacy Risk Assessment of Individual Psychometric Profiles”, in Discovery Science - 24th International Conference, DS 2021, Halifax, NS, Canada, October 11-13, 2021, Proceedings, 2021.
G. Cornacchia and Pappalardo, L., “STS-EPR: Modelling individual mobility considering the spatial, temporal, and social dimensions together”, 2021.
V. Morini, Pollacci, L., and Rossetti, G., “Toward a Standard Approach for Echo Chamber Detection: Reddit Case Study”, Applied Sciences, vol. 11, p. 5390, 2021.

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