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S. Rinzivillo and Ruggieri, S., “Who/Where Are My New Customers?”, in ISMIS Industrial Session, 2011, pp. 307-317.
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.
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.
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.
D. Pedreschi and Ruggieri, S., “Weakest Preconditions for Pure Prolog Programs”, Inf. Process. Lett., vol. 67, pp. 145-150, 1998.
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D. Pedreschi and Ruggieri, S., “Verification of Meta-Interpreters”, J. Log. Comput., vol. 7, pp. 267-303, 1997.
D. Pedreschi and Ruggieri, S., “Verification of Logic Programs”, J. Log. Program., vol. 39, pp. 125-176, 1999.
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S. Ruggieri, “Using t-closeness anonymity to control for non-discrimination.”, Trans. Data Privacy, vol. 7, pp. 99–129, 2014.
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S. Ruggieri and Mesnard, F., “Typing Linear Constraints for Moding CLP() Programs”, in SAS, 2008, pp. 128-143.
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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.
R. Guidotti and Ruggieri, S., “On The Stability of Interpretable Models”, in 2019 International Joint Conference on Neural Networks (IJCNN), 2019.
A. Baroni and Ruggieri, S., “Segregation discovery in a social network of companies”, Journal of Intelligent Information Systems, 2017.
A. Baroni and Ruggieri, S., “Segregation Discovery in a Social Network of Companies”, in International Symposium on Intelligent Data Analysis, 2015.
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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.
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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.
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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.
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A. Romei and Ruggieri, S., “A multidisciplinary survey on discrimination analysis”, The Knowledge Engineering Review, vol. 29, pp. 582–638, 2014.
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.
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.
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.
D. Pedreschi, Ruggieri, S., and Turini, F., “Measuring Discrimination in Socially-Sensitive Decision Records”, in SDM, 2009, pp. 581-592.
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.
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D. Pedreschi and Ruggieri, S., “On Logic Programs That Do Not Fail”, Electr. Notes Theor. Comput. Sci., vol. 30, 1999.
D. Pedreschi and Ruggieri, S., “On logic programs that always succeed”, Sci. Comput. Program., vol. 48, pp. 163-196, 2003.
R. Guidotti, Monreale, A., Ruggieri, S., Pedreschi, D., Turini, F., and Giannotti, F., “Local Rule-Based Explanations of Black Box Decision Systems”, 2018.

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