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S. Ruggieri, Learning from polyhedral sets, in Proceedings of the Twenty-Third international joint conference on Artificial Intelligence, 2013.
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.
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 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, Data Anonymity Meets Non-discrimination, in Data Mining Workshops (ICDMW), 2013 IEEE 13th International Conference on, 2013.
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.
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.
G. Rossetti, Pedreschi, D., and Giannotti, F., Node-centric Community Discovery: From static to dynamic social network analysis, Online Social Networks and Media, vol. 3, pp. 32–48, 2017.
G. Rossetti, Milli, L., and Cazabet, R., CDLIB: a python library to extract, compare and evaluate communities from complex networks, Applied Network Science, vol. 4, p. 52, 2019.
G. Rossetti, Milli, L., Rinzivillo, S., Sirbu, A., Pedreschi, D., and Giannotti, F., NDlib: a python library to model and analyze diffusion processes over complex networks, International Journal of Data Science and Analytics, vol. 5, pp. 61–79, 2018.
G. Rossetti, Pappalardo, L., and Pedreschi, D., Measuring tie strength in multidimensional networks, in SEDB 2013, 2013.
G. Rossetti, Guidotti, R., Miliou, I., Pedreschi, D., and Giannotti, F., A supervised approach for intra-/inter-community interaction prediction in dynamic social networks, Social Network Analysis and Mining, vol. 6, p. 86, 2016.
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, Berlingerio, M., and Giannotti, F., Scalable Link Prediction on Multidimensional Networks, in ICDM Workshops, Vancouver, 2011, pp. 979-986.
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, ANGEL: efficient, and effective, node-centric community discovery in static and dynamic networks, Applied Network Science, vol. 5, pp. 1–23, 2020.

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