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Journal Article
R. Guidotti and Ruggieri, S., Assessing the Stability of Interpretable Models, arXiv preprint arXiv:1810.09352, 2018.
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.
S. Bergamaschi, Carlini, E., Ceci, M., Furletti, B., Giannotti, F., Malerba, D., Mezzanzanica, M., Monreale, A., Pasi, G., Pedreschi, D., Perego, R., and Ruggieri, S., Big Data Research in Italy: A Perspective, Engineering, vol. 2, p. 163, 2016.
D. Pedreschi and Ruggieri, S., Bounded Nondeterminism of Logic Programs, Ann. Math. Artif. Intell., vol. 42, pp. 313-343, 2004.
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., 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, vol. 54, pp. 425 - 437, 2020.
D. Pedreschi, Ruggieri, S., and Smaus, J. - G., Classes of Terminating Logic Programs, CoRR, vol. cs.LO/0106, 2001.
D. Pedreschi, Ruggieri, S., and Smaus, J. - G., Classes of terminating logic programs, TPLP, vol. 2, pp. 369-418, 2002.
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.
M. Aldinucci, Ruggieri, S., and Torquati, M., Decision tree building on multi-core using FastFlow, Concurrency and Computation: Practice and Experience, vol. 26, pp. 800–820, 2014.
A. Romei, Ruggieri, S., and Turini, F., Discrimination discovery in scientific project evaluation: A case study, Expert Systems with Applications, vol. 40, pp. 6064–6079, 2013.
A. Baroni, Conte, A., Patrignani, M., and Ruggieri, S., Efficiently Clustering Very Large Attributed Graphs, arXiv preprint arXiv:1703.08590, 2017.
F. Lillo and Ruggieri, S., Estimating the Total Volume of Queries to a Search Engine, IEEE Transactions on Knowledge and Data Engineering, pp. 1-1, 2021.
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.
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.
S. Mascetti, Ricci, A., and Ruggieri, S., Introduction to special issue on computational methods for enforcing privacy and fairness in the knowledge society, Artificial Intelligence and Law, vol. 22, pp. 109–111, 2014.
S. Ruggieri, Introduction to the special issue on Artificial Intelligence for Society and Economy, Intelligenza Artificiale, vol. 9, pp. 23–23, 2015.
D. Pedreschi and Ruggieri, S., On logic programs that always succeed, Sci. Comput. Program., vol. 48, pp. 163-196, 2003.
D. Pedreschi and Ruggieri, S., On Logic Programs That Do Not Fail, Electr. Notes Theor. Comput. Sci., vol. 30, 1999.
C. Renso and Ruggieri, S., A Mediator Approach for Representing Knowledge, Intelligent Multimedia Presentation Systems. Human Computer Interaction Letters, 1 (1): 32-38, April 1998., 1998.
A. Romei and Ruggieri, S., A multidisciplinary survey on discrimination analysis, The Knowledge Engineering Review, vol. 29, pp. 582–638, 2014.
P. Eirinakis, Ruggieri, S., Subramani, K., and Wojciechowski, P., On quantified linear implications, Annals of Mathematics and Artificial Intelligence, vol. 71, pp. 301–325, 2014.
A. Baroni and Ruggieri, S., Segregation discovery in a social network of companies, Journal of Intelligent Information Systems, 2017.
R. Guidotti, Monreale, A., Ruggieri, S., Turini, F., Giannotti, F., and Pedreschi, D., A survey of methods for explaining black box models, ACM computing surveys (CSUR), vol. 51, p. 93, 2018.