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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.
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.
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.
B. Qureshi, Kamiran, F., Karim, A., Ruggieri, S., and Pedreschi, D., Causal inference for social discrimination reasoning, vol. 54, pp. 425 - 437, 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.
N. Forgó, Hänold, S., van den Hoven, J., Krügel, T., Lishchuk, I., Mahieu, R., Monreale, A., Pedreschi, D., Pratesi, F., and van Putten, D., An ethico-legal framework for social data science, 2020.
A. Sirbu, Andrienko, G., Andrienko, N., Boldrini, C., Conti, M., Giannotti, F., Guidotti, R., Bertoli, S., Kim, J., Muntean, C. Ioana, Pappalardo, L., Passarella, A., Pedreschi, D., Pollacci, L., Pratesi, F., and Sharma, R., Human migration: the big data perspective, International Journal of Data Science and Analytics, pp. 1–20, 2020.
P. Bonato, Cintia, P., Fabbri, F., Fadda, D., Giannotti, F., Lopalco, P. Luigi, Mazzilli, S., Nanni, M., Pappalardo, L., Pedreschi, D., Penone, F., Rinzivillo, S., Rossetti, G., Savarese, M., and Tavoschi, L., Mobile phone data analytics against the COVID-19 epidemics in Italy: flow diversity and local job markets during the national lockdown. 2020.
P. Cintia, Fadda, D., Giannotti, F., Pappalardo, L., Rossetti, G., Pedreschi, D., Rinzivillo, S., Bonato, P., Fabbri, F., Penone, F., Savarese, M., Checchi, D., Chiaromonte, F., Vineis, P., Guzzetta, G., Riccardo, F., Marziano, V., Poletti, P., Trentini, F., Bella, A., Andrianou, X., Del Manso, M., Fabiani, M., Bellino, S., Boros, S., Urdiales, A. Mateo, Vescio, M. Fenicia, Brusaferro, S., Rezza, G., Pezzotti, P., Ajelli, M., and Merler, S., The relationship between human mobility and viral transmissibility during the COVID-19 epidemics in Italy, arXiv preprint arXiv:2006.03141, 2020.
2019
R. Guidotti, Monreale, A., and Pedreschi, D., The AI black box Explanation Problem, ERCIM NEWS, pp. 12–13, 2019.
A. Sirbu, Pedreschi, D., Giannotti, F., and Kertész, J., Algorithmic bias amplifies opinion fragmentation and polarization: A bounded confidence model, PloS one, vol. 14, p. e0213246, 2019.
B. Qureshi, Kamiran, F., Karim, A., Ruggieri, S., and Pedreschi, D., Causal inference for social discrimination reasoning, Journal of Intelligent Information Systems, pp. 1–13, 2019.
C. Panigutti, Guidotti, R., Monreale, A., and Pedreschi, D., Explaining multi-label black-box classifiers for health applications, in International Workshop on Health Intelligence, 2019.
R. Guidotti, Monreale, A., Giannotti, F., Pedreschi, D., Ruggieri, S., and Turini, F., Factual and Counterfactual Explanations for Black Box Decision Making, IEEE Intelligent Systems, 2019.
D. Pedreschi, Giannotti, F., Guidotti, R., Monreale, A., Ruggieri, S., and Turini, F., Meaningful explanations of Black Box AI decision systems, in Proceedings of the AAAI Conference on Artificial Intelligence, 2019.
L. Pappalardo, Cintia, P., Ferragina, P., Massucco, E., Pedreschi, D., and Giannotti, F., PlayeRank: data-driven performance evaluation and player ranking in soccer via a machine learning approach, ACM Transactions on Intelligent Systems and Technology (TIST), vol. 10, pp. 1–27, 2019.

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