A reductions approach to fair classification, 2018. ,
Fair regression: Quantitative definitions and reduction-based algorithms, International Conference on Machine Learning, 2019. ,
Data-driven calibration of linear estimators with minimal penalties, Advances in Neural Information Processing Systems, pp.46-54, 2009. ,
URL : https://hal.archives-ouvertes.fr/hal-00414774
Fairness and Machine Learning. fairmlbook.org, 2018. ,
A fast iterative shrinkage-thresholding algorithm for linear inverse problems, SIAM journal on imaging sciences, vol.2, issue.1, pp.183-202, 2009. ,
A convex framework for fair regression, Fairness, Accountability, and Transparency in Machine Learning, 2017. ,
Simultaneous analysis of Lasso and Dantzig selector, Ann. Statist, vol.37, issue.4, pp.1705-1732, 2009. ,
URL : https://hal.archives-ouvertes.fr/hal-00401585
Learnability and the Vapnik-Chervonenkis dimension, Journal of the ACM, vol.36, issue.4, pp.929-965, 1989. ,
Consistency for a simple model of random forests, 2004. ,
, Bureau of Labor Statistics. National longitudinal surveys of youth data set, 2019.
Building classifiers with independency constraints, IEEE international conference on Data mining, 2009. ,
Controlling attribute effect in linear regression, IEEE International Conference on Data Mining, 2013. ,
Optimized pre-processing for discrimination prevention, Neural Information Processing Systems, 2017. ,
Fair clustering through fairlets, Neural Information Processing Systems, 2017. ,
Plug-in methods in classification, 2019. ,
URL : https://hal.archives-ouvertes.fr/tel-02400552
Minimax semi-supervised confidence sets for multi-class classification, 2019. ,
URL : https://hal.archives-ouvertes.fr/hal-02112918
Leveraging labeled and unlabeled data for consistent fair binary classification, Advances in Neural Information Processing Systems, vol.32, pp.12739-12750, 2019. ,
URL : https://hal.archives-ouvertes.fr/hal-02150662
Using data mining to predict secondary school student performance, FUture BUsiness TEChnology Conference, 2008. ,