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R. Guidotti and Ruggieri, S., Assessing the Stability of Interpretable Models, arXiv preprint arXiv:1810.09352, 2018.
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 Saccà, D., Eds. Cham: Springer International Publishing, 2018, pp. 287 - 306.
R. Guidotti, Monreale, A., Ruggieri, S., Pedreschi, D., Turini, F., and Giannotti, F., Local Rule-Based Explanations of Black Box Decision Systems, 2018.
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.
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.
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.