Fair-n: Fair and robust neural networks for structured data

S Sharma, AH Gee, D Paydarfar, J Ghosh - Proceedings of the 2021 …, 2021 - dl.acm.org
Fairness and robustness in machine learning are crucial when individuals are subject to
automated decisions made by models in high-stake domains. To promote ethical artificial …
被引用次数：18 相关文章

FaiR-N: Fair and Robust Neural Networks for Structured Data

S Sharma, AH Gee, D Paydarfar, J Ghosh - arXiv e-prints, 2020 - ui.adsabs.harvard.edu
Fairness in machine learning is crucial when individuals are subject to automated decisions
made by models in high-stake domains. Organizations that employ these models may also …
[PDF] academia.edu

[PDF][PDF] FaiR-N: Fair and Robust Neural Networks for Structured Data

S Sharma, AH Gee, D Paydarfar, J Ghosh - academia.edu
Fairness in machine learning is crucial when individuals are subject to automated decisions
made by models in high-stake domains. Organizations that employ these models may also …

FaiR-N: Fair and Robust Neural Networks for Structured Data

S Sharma, A Gee, D Paydarfar, J Ghosh - aies-conference.com
• FaiR-N uses a novel distance to the boundary formulation in order to:-reduce the disparity
in the average ability of recourse (ie the change needed to get a positive outcome) between …

FaiR-N: Fair and Robust Neural Networks for Structured Data

S Sharma, AH Gee, D Paydarfar, J Ghosh - arXiv preprint arXiv …, 2020 - arxiv.org
Fairness in machine learning is crucial when individuals are subject to automated decisions
made by models in high-stake domains. Organizations that employ these models may also …