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2024
L. Corbucci, Heikkila, M. A., Noguero, D. Solans, Monreale, A., and Kourtellis, N., “PUFFLE: Balancing Privacy, Utility, and Fairness in Federated Learning”, 2024.
2023
A. Knott, Pedreschi, D., Chatila, R., Chakraborti, T., Leavy, S., Baeza-Yates, R., Eyers, D., Trotman, A., Teal, P. D., Biecek, P., Russell, S., and Bengio, Y., “Generative AI models should include detection mechanisms as a condition for public releaseAbstract”, Ethics and Information Technology, vol. 25, 2023.
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. 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.
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.
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.
B. Qureshi, Kamiran, F., Karim, A., Ruggieri, S., and Pedreschi, D., “Causal inference for social discrimination reasoning”, vol. 54, pp. 425 - 437, 2020.
B. Qureshi, Kamiran, F., Karim, A., Ruggieri, S., and Pedreschi, D., “Causal inference for social discrimination reasoning”, vol. 54, pp. 425 - 437, 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.
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.
R. Guidotti and Rossetti, G., ““Know Thyself” How Personal Music Tastes Shape the Last.Fm Online Social Network”, in Formal Methods. FM 2019 International Workshops, Cham, 2020.
F. Naretto, Pellungrini, R., Nardini, F. Maria, and Giannotti, F., “Prediction and Explanation of Privacy Risk on Mobility Data with Neural Networks”, in ECML PKDD 2020 Workshops, Cham, 2020.
F. Naretto, Pellungrini, R., Nardini, F. Maria, and Giannotti, F., “Prediction and Explanation of Privacy Risk on Mobility Data with Neural Networks”, in ECML PKDD 2020 Workshops, Cham, 2020.
F. Naretto, Pellungrini, R., Nardini, F. Maria, and Giannotti, F., “Prediction and Explanation of Privacy Risk on Mobility Data with Neural Networks”, in ECML PKDD 2020 Workshops, Cham, 2020.
F. Naretto, Pellungrini, R., Nardini, F. Maria, and Giannotti, F., “Prediction and Explanation of Privacy Risk on Mobility Data with Neural Networks”, in ECML PKDD 2020 Workshops, Cham, 2020.
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.
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.
A. Sirbu, Giannotti, F., Pedreschi, D., and Kertész, J., “Public opinion and Algorithmic bias”, ERCIM News, 2019.
2017
M. Nanni, Kotthoff, L., Guidotti, R., O'Sullivan, B., and Pedreschi, D., “ICON Loop Carpooling Show Case”, Data Mining and Constraint Programming: Foundations of a Cross-Disciplinary Approach, vol. 10101, p. 310, 2017.
C. Bessiere, De Raedt, L., Guns, T., Kotthoff, L., Nanni, M., Nijssen, S., O'Sullivan, B., Paparrizou, A., Pedreschi, D., and Simonis, H., “The Inductive Constraint Programming Loop”, IEEE Intelligent Systems, 2017.
2016
B. Qureshi, Kamiran, F., Karim, A., and Ruggieri, S., “Causal Discrimination Discovery Through Propensity Score Analysis”, arXiv preprint arXiv:1608.03735, 2016.
B. Qureshi, Kamiran, F., Karim, A., and Ruggieri, S., “Causal Discrimination Discovery Through Propensity Score Analysis”, arXiv preprint arXiv:1608.03735, 2016.

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