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V. D. P. Servedio, Caminiti, S., Gravino, P., Loreto, V., Sirbu, A., and Tria, F., “Large Scale Engagement Through Web-Gaming and Social Computations”, in Participatory Sensing, Opinions and Collective Awareness, Springer, 2017, pp. 237–254.
R. Portocarre Sarmento, Lemos, L., Cordeiro, M., Rossetti, G., and Cardoso, D., “DynComm R Package–Dynamic Community Detection for Evolving Networks”, arXiv preprint arXiv:1905.01498, 2019.
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S. Ruggieri, “Using t-closeness anonymity to control for non-discrimination.”, Trans. Data Privacy, vol. 7, pp. 99–129, 2014.
S. Ruggieri, Eirinakis, P., Subramani, K., and Wojciechowski, P., “On the complexity of quantified linear systems”, Theoretical Computer Science, vol. 518, pp. 128–134, 2014.
S. Ruggieri and Mesnard, F., “Typing Linear Constraints for Moding CLP() Programs”, in SAS, 2008, pp. 128-143.
S. Ruggieri, “Data Anonymity Meets Non-discrimination”, in Data Mining Workshops (ICDMW), 2013 IEEE 13th International Conference on, 2013.
S. Ruggieri, “Learning from polyhedral sets”, in Proceedings of the Twenty-Third international joint conference on Artificial Intelligence, 2013.
S. Ruggieri and Turini, F., “A KDD process for discrimination discovery”, in Joint European Conference on Machine Learning and Knowledge Discovery in Databases, 2016.
S. Ruggieri, “Enumerating Distinct Decision Trees”, in International Conference on Machine Learning, 2017.
S. Ruggieri, “Introduction to the special issue on Artificial Intelligence for Society and Economy”, Intelligenza Artificiale, vol. 9, pp. 23–23, 2015.
S. Ruggieri, Hajian, S., Kamiran, F., and Zhang, X., “Anti-discrimination analysis using privacy attack strategies”, in Joint European Conference on Machine Learning and Knowledge Discovery in Databases, 2014.
A. Rossi, Pappalardo, L., Cintia, P., F Iaia, M., Fernàndez, J., and Medina, D., “Effective injury forecasting in soccer with GPS training data and machine learning”, PloS one, vol. 13, p. e0201264, 2018.
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.
A. Rossi, Perri, E., Pappalardo, L., Cintia, P., and F Iaia, M., “Relationship between External and Internal Workloads in Elite Soccer Players: Comparison between Rate of Perceived Exertion and Training Load”, Applied Sciences, vol. 9, p. 5174, 2019.
G. Rossetti, Citraro, S., and Milli, L., “Conformity: A Path-Aware Homophily Measure for Node-Attributed Networks”, arXiv preprint arXiv:2012.05195, 2020.
G. Rossetti, Milli, L., Citraro, S., and Morini, V., “UTLDR: an agent-based framework for modeling infectious diseases and public interventions”, arXiv preprint arXiv:2011.05606, 2020.
G. Rossetti, Pappalardo, L., Pedreschi, D., and Giannotti, F., “Tiles: an online algorithm for community discovery in dynamic social networks”, Machine Learning, vol. 106, pp. 1213–1241, 2017.
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.
G. Rossetti, Guidotti, R., Pennacchioli, D., Pedreschi, D., and Giannotti, F., “Interaction Prediction in Dynamic Networks exploiting Community Discovery”, in International conference on Advances in Social Network Analysis and Mining, ASONAM 2015, Paris, France, 2015.
G. Rossetti, “ANGEL: efficient, and effective, node-centric community discovery in static and dynamic networks”, Applied Network Science, vol. 5, pp. 1–23, 2020.
G. Rossetti, Morini, V., and Pollacci, L., “Capturing Political Polarization of Reddit Submissions in the Trump Era”, in SEBD, 2020.
G. Rossetti, Pappalardo, L., Kikas, R., Pedreschi, D., Giannotti, F., and Dumas, M., “Community-centric analysis of user engagement in Skype social network”, in International conference on Advances in Social Network Analysis and Mining, Paris, France, 2015.
G. Rossetti, “Exorcising the Demon: Angel, Efficient Node-Centric Community Discovery”, in International Conference on Complex Networks and Their Applications, 2019.
G. Rossetti, Pappalardo, L., Kikas, R., Pedreschi, D., Giannotti, F., and Dumas, M., “Homophilic network decomposition: a community-centric analysis of online social services”, Social Network Analysis and Mining, vol. 6, p. 103, 2016.
G. Rossetti and Cazabet, R., “Community Discovery in Dynamic Networks: a Survey”, Journal ACM Computing Surveys, vol. 51, 2018.

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