Publications

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2021
F. Giannotti, Naretto, F., and Bodria, F., Explainable for Trustworthy AI, in Human-Centered Artificial Intelligence - Advanced Lectures, 18th European Advanced Course on AI, ACAI 2021, Berlin, Germany, October 11-15, 2021, extended and improved lecture notes, 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 2021 18th International Conference on Privacy, Security and Trust (PST), 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.
V. Lorenzoni, Triulzi, I., Martinucci, I., Toncelli, L., Natilli, M., Barale, R., and Turchetti, G., Understanding eating choices among university students: A study using data from cafeteria cashiers’ transactions, Health Policy, vol. 125, pp. 665–673, 2021.
2020
M. Natilli, Fadda, D., Rinzivillo, S., Pedreschi, D., and Licari, F., Analysis and Visualization of Performance Indicators in University Admission Tests, in Formal Methods. FM 2019 International Workshops, Cham, 2020.
G. Rossetti, ANGEL: efficient, and effective, node-centric community discovery in static and dynamic networks, Applied Network Science, vol. 5, pp. 1–23, 2020.
D. Pedreschi and Miliou, I., Artificial Intelligence (AI): new developments and innovations applied to e-commerce, European Parliament's committee on the Internal Market and Consumer Protection, 2020.
B. Dong, Wang, H., Monreale, A., Pedreschi, D., Giannotti, F., and Guo, W., Authenticated Outlier Mining for Outsourced Databases, IEEE Transactions on Dependable and Secure Computing, vol. 17, pp. 222 - 235, 2020.
E. Ntoutsi, Fafalios, P., Gadiraju, U., Iosifidis, V., Nejdl, W., Vidal, M. - E., Ruggieri, S., Turini, F., Papadopoulos, S., Krasanakis, E., and others, Bias in data-driven artificial intelligence systems—An introductory survey, Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, vol. 10, p. e1356, 2020.
R. Guidotti, Monreale, A., Matwin, S., and Pedreschi, D., Black Box Explanation by Learning Image Exemplars in the Latent Feature Space, in Machine Learning and Knowledge Discovery in Databases, Cham, 2020.
G. Rossetti, Morini, V., and Pollacci, L., Capturing Political Polarization of Reddit Submissions in the Trump Era, in SEBD, 2020.
B. Qureshi, Kamiran, F., Karim, A., Ruggieri, S., and Pedreschi, D., Causal inference for social discrimination reasoning, vol. 54, pp. 425 - 437, 2020.
G. Rossetti, Citraro, S., and Milli, L., Conformity: A Path-Aware Homophily Measure for Node-Attributed Networks, arXiv preprint arXiv:2012.05195, 2020.
J. Kim, Sirbu, A., Giannotti, F., and Gabrielli, L., Digital Footprints of International Migration on Twitter, in International Symposium on Intelligent Data Analysis, 2020.
C. Panigutti, Perotti, A., and Pedreschi, D., Doctor XAI: an ontology-based approach to black-box sequential data classification explanations, in Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency, 2020.
A. Rossi, Pedreschi, D., Clifton, D. A., and Morelli, D., Error Estimation of Ultra-Short Heart Rate Variability Parameters: Effect of Missing Data Caused by Motion Artifacts, Sensors, vol. 20, p. 7122, 2020.
V. Voukelatou, Pappalardo, L., Gabrielli, L., and Giannotti, F., Estimating countries’ peace index through the lens of the world news as monitored by GDELT, in 2020 IEEE 7th International Conference on Data Science and Advanced Analytics (DSAA)2020 IEEE 7th International Conference on Data Science and Advanced Analytics (DSAA), 2020.

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