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English Information

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Authors
# Name
1 Maria Silva(malu.maia@lsbd.ufc.br)
2 Javam Machado(javam.machado@lsbd.ufc.br)

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Reference
# Reference
1 Angwin, J., Larson, J., Mattu, S., , and Kirchner, L. (2016). Machine bias, ProPublica.
2 Barocas, S., Hardt, M., and Narayanan, A. (2017). Fairness in machine learning. Nips tutorial, 1:2017.
3 Dua, D. and Graff, C. (2017). UCI machine learning repository.
4 Dwork, C. (2006). Differential privacy. In International Colloquium on Automata, Languages, and Programming, pages 1–12. Springer.
5 Dwork, C., Hardt, M., Pitassi, T., Reingold, O., and Zemel, R. (2012). Fairness through awareness. In Proceedings of the 3rd innovations in theoretical computer science conference, pages 214–226.
6 Elbassuoni, S., Amer-Yahia, S., and Ghizzawi, A. (2020). Fairness of scoring in online job marketplaces. Trans. Data Sci., 1(4):29:1–29:30.
7 Lee, M. S. A. and Floridi, L. (2021). Algorithmic fairness in mortgage lending: from absolute conditions to relational trade-offs. Minds Mach., 31(1):165–191.
8 Newcombe, H. B., Kennedy, J. M., Axford, S., and James, A. P. (1959). Automatic linkage of vital records. Science, 130(3381):954–959.
9 Pujol, D., McKenna, R., Kuppam, S., Hay, M., Machanavajjhala, A., and Miklau, G. (2020). Fair decision making using privacy-protected data. In Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency, pages 189–199.
10 Quinlan, J. R. (1986). Induction of decision trees. Machine learning, 1(1):81–106.
11 Ranzato, F., Urban, C., and Zanella, M. (2021). Fair training of decision tree classifiers. arXiv preprint arXiv:2101.00909.
12 Xu, D., Yuan, S., and Wu, X. (2019). Achieving differential privacy and fairness in logistic regression. In Companion Proceedings of The 2019 World Wide Web Conference, pages 594–599.