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A.  Pugnana and Ruggieri, S., ?AUC-based Selective Classification?, in International Conference on Artificial Intelligence and Statistics, 25-27 April 2023, Palau de Congressos, Valencia, Spain, 2023.\par \par A.  Pugnana and Ruggieri, S., ?A Model-Agnostic Heuristics for Selective Classification?, in Thirty-Seventh AAAI Conference on Artificial Intelligence, AAAI 2023, 2023, Washington, DC, USA, February 7-14, 2023, 2023.\par \par A. Rita Nogueira, Pugnana, A., Ruggieri, S., Pedreschi, D., and Gama, J., ?Methods and tools for causal discovery and causal inference?, WIREs Data Mining Knowl. Discov., vol. 12, 2022.\par \par 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.\par \par M.  Nanni, Andrienko, G., Barabasi, A. - L., Boldrini, C., Bonchi, F., Cattuto, C., Chiaromonte, F., Comand\'e9, G., Conti, M., Cot\'e9, M., Dignum, F., Dignum, V., Domingo-Ferrer, J., Ferragina, P., Giannotti, F., Guidotti, R., Helbing, D., Kaski, K., Kert\'e9sz, J., Lehmann, S., Lepri, B., Lukowicz, P., Matwin, S., Jim\'e9nez, D. Meg\'edas, 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.\par \par 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.\par \par B.  Qureshi, Kamiran, F., Karim, A., Ruggieri, S., and Pedreschi, D., ?Causal inference for social discrimination reasoning?, vol. 54, pp. 425 - 437, 2020.\par \par O.  Lampridis, Guidotti, R., and Ruggieri, S., ?Explaining Sentiment Classification with Synthetic Exemplars and Counter-Exemplars?, in Discovery Science, Cham, 2020.\par \par 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.\par \par 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.\par \par D.  Pedreschi, Giannotti, F., Guidotti, R., Monreale, A., Ruggieri, S., and Turini, F., ?Meaningful explanations of Black Box AI decision systems?, in Proceedings of the AAAI Conference on Artificial Intelligence, 2019.\par \par R.  Guidotti and Ruggieri, S., ?On The Stability of Interpretable Models?, in 2019 International Joint Conference on Neural Networks (IJCNN), 2019.\par \par R.  Guidotti and Ruggieri, S., ?Assessing the Stability of Interpretable Models?, arXiv preprint arXiv:1810.09352, 2018.\par \par G.  Amato, Candela, L., Castelli, D., Esuli, A., Falchi, F., Gennaro, C., Giannotti, F., Monreale, A., Nanni, M., Pagano, P., Pappalardo, L., Pedreschi, D., Pratesi, F., Rabitti, F., Rinzivillo, S., Rossetti, G., Ruggieri, S., Sebastiani, F., and Tesconi, M., ?How Data Mining and Machine Learning Evolved from Relational Data Base to Data Science?, in A Comprehensive Guide Through the Italian Database Research Over the Last 25 Years, S.  Flesca, Greco, S., Masciari, E., and Sacc\'e0, D., Eds. Cham: Springer International Publishing, 2018, pp. 287 - 306.\par \par R.  Guidotti, Monreale, A., Ruggieri, S., Pedreschi, D., Turini, F., and Giannotti, F., ?Local Rule-Based Explanations of Black Box Decision Systems?, 2018.\par \par D.  Pedreschi, Giannotti, F., Guidotti, R., Monreale, A., Pappalardo, L., Ruggieri, S., and Turini, F., ?Open the Black Box Data-Driven Explanation of Black Box Decision Systems?, 2018.\par \par 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.\par \par A.  Baroni, Conte, A., Patrignani, M., and Ruggieri, S., ?Efficiently Clustering Very Large Attributed Graphs?, arXiv preprint arXiv:1703.08590, 2017.\par \par S.  Ruggieri, ?Enumerating Distinct Decision Trees?, in International Conference on Machine Learning, 2017.\par \par A.  Baroni and Ruggieri, S., ?Segregation discovery in a social network of companies?, Journal of Intelligent Information Systems, 2017.\par \par 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.\par \par B.  Qureshi, Kamiran, F., Karim, A., and Ruggieri, S., ?Causal Discrimination Discovery Through Propensity Score Analysis?, arXiv preprint arXiv:1608.03735, 2016.\par \par B. Thanh Luong, Ruggieri, S., and Turini, F., ?Classification Rule Mining Supported by Ontology for Discrimination Discovery?, in Data Mining Workshops (ICDMW), 2016 IEEE 16th International Conference on, 2016.\par \par S.  Ruggieri and Turini, F., ?A KDD process for discrimination discovery?, in Joint European Conference on Machine Learning and Knowledge Discovery in Databases, 2016.\par \par S.  Ruggieri, ?Introduction to the special issue on Artificial Intelligence for Society and Economy?, Intelligenza Artificiale, vol. 9, pp. 23?23, 2015.\par \par A.  Romei, Ruggieri, S., and Turini, F., ?The layered structure of company share networks?, in Data Science and Advanced Analytics (DSAA), 2015. 36678 2015. IEEE International Conference on, 2015.\par \par A.  Baroni and Ruggieri, S., ?Segregation Discovery in a Social Network of Companies?, in International Symposium on Intelligent Data Analysis, 2015.\par \par 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.\par \par 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.\par \par 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.\par \par 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.\par \par A.  Romei and Ruggieri, S., ?A multidisciplinary survey on discrimination analysis?, The Knowledge Engineering Review, vol. 29, pp. 582?638, 2014.\par \par 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.\par \par S.  Ruggieri, ?Using t-closeness anonymity to control for non-discrimination.?, Trans. Data Privacy, vol. 7, pp. 99?129, 2014.\par \par S.  Ruggieri, ?Data Anonymity Meets Non-discrimination?, in Data Mining Workshops (ICDMW), 2013 IEEE 13th International Conference on, 2013.\par \par D.  Pedreschi, Ruggieri, S., and Turini, F., ?The discovery of discrimination?, in Discrimination and privacy in the information society, Springer, 2013, pp. 91?108.\par \par 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.\par \par S.  Ruggieri, ?Learning from polyhedral sets?, in Proceedings of the Twenty-Third international joint conference on Artificial Intelligence, 2013.\par \par S.  Rinzivillo and Ruggieri, S., ?Who/Where Are My New Customers??, in ISMIS Industrial Session, 2011, pp. 307-317.\par \par D.  Pedreschi, Ruggieri, S., and Turini, F., ?Integrating induction and deduction for finding evidence of discrimination?, in ICAIL, 2009, pp. 157-166.\par \par D.  Pedreschi, Ruggieri, S., and Turini, F., ?Measuring Discrimination in Socially-Sensitive Decision Records?, in SDM, 2009, pp. 581-592.\par \par V.  Grossi, Romei, A., and Ruggieri, S., ?A Case Study in Sequential Pattern Mining for IT-Operational Risk?, in ECML/PKDD (1), 2008, pp. 424-439.\par \par D.  Pedreschi, Ruggieri, S., and Turini, F., ?Discrimination-aware data mining?, in KDD, 2008, pp. 560-568.\par \par S.  Ruggieri and Mesnard, F., ?Typing Linear Constraints for Moding CLP() Programs?, in SAS, 2008, pp. 128-143.\par \par D.  Pedreschi and Ruggieri, S., ?Bounded Nondeterminism of Logic Programs?, Ann. Math. Artif. Intell., vol. 42, pp. 313-343, 2004.\par \par D.  Pedreschi, Ruggieri, S., and Smaus, J. - G., ?Characterisations of Termination in Logic Programming?, in Program Development in Computational Logic, 2004, pp. 376-431.\par \par D.  Pedreschi and Ruggieri, S., ?On logic programs that always succeed?, Sci. Comput. Program., vol. 48, pp. 163-196, 2003.\par \par D.  Pedreschi, Ruggieri, S., and Smaus, J. - G., ?Classes of terminating logic programs?, TPLP, vol. 2, pp. 369-418, 2002.\par \par P.  Mancarella, Pedreschi, D., and Ruggieri, S., ?Negation as Failure through Abduction: Reasoning about Termination?, in Computational Logic: Logic Programming and Beyond, 2002, pp. 240-272.\par \par D.  Pedreschi, Ruggieri, S., and Smaus, J. - G., ?Classes of Terminating Logic Programs?, CoRR, vol. cs.LO/0106, 2001.\par \par F.  Bonchi, Giannotti, F., Manco, G., Renso, C., Nanni, M., Pedreschi, D., and Ruggieri, S., ?Data Mining for Intelligent Web Caching?, in ITCC, 2001, pp. 599-603.\par \par F.  Bonchi, Giannotti, F., Manco, G., Renso, C., Nanni, M., Pedreschi, D., and Ruggieri, S., ?Data Mining for Intelligent Web Caching?, in ITCC, 2001, pp. 599-603.\par \par F.  Bonchi, Giannotti, F., Gozzi, C., Manco, G., Nanni, M., Pedreschi, D., Renso, C., and Ruggieri, S., ?Web Log Data Warehousing and Mining for Intelligent Web Caching?, Data and Knowledge Engineering, 2001.\par \par F.  Bonchi, Giannotti, F., Gozzi, C., Manco, G., Nanni, M., Pedreschi, D., Renso, C., and Ruggieri, S., ?Web log data warehousing and mining for intelligent web caching?, Data Knowl. Eng., vol. 39, pp. 165-189, 2001.\par \par F.  Bonchi, Giannotti, F., Gozzi, C., Manco, G., Nanni, M., Pedreschi, D., Renso, C., and Ruggieri, S., ?Web log data warehousing and mining for intelligent web caching?, Data Knowl. Eng., vol. 39, pp. 165-189, 2001.\par \par D.  Pedreschi and Ruggieri, S., ?Bounded Nondeterminism of Logic Programs?, in ICLP, 1999, pp. 350-364.\par \par D.  Pedreschi and Ruggieri, S., ?On Logic Programs That Do Not Fail?, Electr. Notes Theor. Comput. Sci., vol. 30, 1999.\par \par D.  Pedreschi and Ruggieri, S., ?Verification of Logic Programs?, J. Log. Program., vol. 39, pp. 125-176, 1999.\par \par 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.\par \par D.  Pedreschi and Ruggieri, S., ?Weakest Preconditions for Pure Prolog Programs?, Inf. Process. Lett., vol. 67, pp. 145-150, 1998.\par \par D.  Pedreschi and Ruggieri, S., ?Verification of Meta-Interpreters?, J. Log. Comput., vol. 7, pp. 267-303, 1997.\par \par D.  Pedreschi and Ruggieri, S., ?A Case Study in Logic Program Verification: the Vanilla Metainterpreter?, in GULP-PRODE, 1995, pp. 643-654.\par \par }