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Liu, Yang

Bibliographic References tagged with Liu, Yang

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Y. Liu, G. Radanovic, C. Dimitrakakis, D. Mandal, and D. C. Parkes,
Calibrated fairness in Bandits”, in Proceedings of the 4th Workshop on Fairness, Accountability, and Transparency in Machine Learning (Fat/ML 2017), 2017.
Y. Liu, G. Radanovic, C. Dimitrakakis, D. Mandal, and D. C. Parkes,
Calibrated fairness in Bandits”, in Proceedings of the 4th Workshop on Fairness, Accountability, and Transparency in Machine Learning (Fat/ML 2017), 2017.
B. Ustun, Y. Liu, and D. C. Parkes,
Fairness without Harm: Decoupled Classifiers with Preference Guarantees”, in Proceedings of the 36th International Conference on Machine Learning (ICML’19), 2019, pp. 6373–6382.
B. Ustun, Y. Liu, and D. C. Parkes,
Fairness without Harm: Decoupled Classifiers with Preference Guarantees”, in Proceedings of the 36th International Conference on Machine Learning (ICML’19), 2019, pp. 6373–6382.
N. Saxena, K. Huang, E. DeFilippis, G. Radanovic, D. Parkes, and Y. Liu,
How Do Fairness Definitions Fare? Examining Public Attitudes Towards Algorithmic Definitions of Fairness”, in Proceedings of AI Ethics and Society (AIES), 2019, pp. 99–106.
N. Saxena, K. Huang, E. DeFilippis, G. Radanovic, D. Parkes, and Y. Liu,
How Do Fairness Definitions Fare? Examining Public Attitudes Towards Algorithmic Definitions of Fairness”, in Proceedings of AI Ethics and Society (AIES), 2019, pp. 99–106.
C. Dimitrakakis, Y. Liu, D. C. Parkes, and G. Radanovic,
Bayesian Fairness”, in Proceedings of the 33rd AAAI Conference on Artificial Intelligence (AAAI), 2019.
C. Dimitrakakis, Y. Liu, D. C. Parkes, and G. Radanovic,
Bayesian Fairness”, in Proceedings of the 33rd AAAI Conference on Artificial Intelligence (AAAI), 2019.
N. A. Saxena, K. Huang, E. DeFilippis, G. Radanovic, Y. Liu, and D. C. Parkes,
N. A. Saxena, K. Huang, E. DeFilippis, G. Radanovic, Y. Liu, and D. C. Parkes,