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G. Rossetti, Milli, L., Giannotti, F., and Pedreschi, D., Forecasting success via early adoptions analysis: A data-driven study, PloS one, vol. 12, p. e0189096, 2017.
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, pp. 1–19, 2017.
G. Rossetti, Milli, L., Rinzivillo, S., Sirbu, A., Pedreschi, D., and Giannotti, F., NDlib: Studying Network Diffusion Dynamics, in IEEE International Conference on Data Science and Advanced Analytics, DSA, Tokyo, 2017.
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, 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.
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.
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 and Mesnard, F., Typing Linear Constraints for Moding CLP() Programs, in SAS, 2008, pp. 128-143.
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, 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.
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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.
M. Setzu and Atzori, M., SPARQL Queries over Source Code, in 2016 IEEE Tenth International Conference on Semantic Computing (ICSC), 2016.
A. Sirbu and Babaoglu, O., Power Consumption Modeling and Prediction in a Hybrid CPU-GPU-MIC Supercomputer, 22nd International European Conference on Parallel and Distributed Computing, Euro-Par 2016, vol. LNCS 9833. Springer LNCS, Grenoble, France, 2016.
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.
A. Sirbu, Crane, M., and Ruskin, H. J., EGIA–Evolutionary Optimisation of Gene Regulatory Networks, an Integrative Approach, in Complex Networks V, Springer International Publishing, 2014, pp. 217–229.
A. Sirbu, Giannotti, F., Pedreschi, D., and Kertész, J., Public opinion and Algorithmic bias, ERCIM News, 2019.
A. Sirbu, Loreto, V., Servedio, V. D. P., and Tria, F., Cohesion, consensus and extreme information in opinion dynamics, Advances in Complex Systems, vol. 16, p. 1350035, 2013.
A. Sirbu, Ruskin, H. J., and Crane, M., Stages of Gene Regulatory Network Inference: the Evolutionary Algorithm Role, in Evolutionary Algorithms, InTech, 2011.

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