Fair Learning with Private Demographic Data

26 February 2020

Papers citing "Fair Learning with Private Demographic Data"

18 / 18 papers shown

Title
Discrimination-free Insurance Pricing with Privatized Sensitive Attributes Tianhe Zhang Suhan Liu Peng Shi FaML 71 0 0 16 Apr 2025
PFGuard: A Generative Framework with Privacy and Fairness Safeguards Soyeon Kim Yuji Roh Geon Heo Steven Euijong Whang 39 0 0 03 Oct 2024
Fairness Risks for Group-conditionally Missing Demographics Kaiqi Jiang Wenzhe Fan Mao Li Xinhua Zhang 105 0 0 20 Feb 2024
On the Fairness Impacts of Private Ensembles Models Cuong Tran Ferdinando Fioretto 41 4 0 19 May 2023
(Local) Differential Privacy has NO Disparate Impact on Fairness Héber H. Arcolezi K. Makhlouf C. Palamidessi 40 6 0 25 Apr 2023
Learning with Impartiality to Walk on the Pareto Frontier of Fairness, Privacy, and Utility Mohammad Yaghini Patty Liu Franziska Boenisch Nicolas Papernot FedML FaML 38 8 0 17 Feb 2023
Hyper-parameter Tuning for Fair Classification without Sensitive Attribute Access A. Veldanda Ivan Brugere Sanghamitra Dutta Alan Mishler S. Garg 39 5 0 02 Feb 2023
Unraveling Privacy Risks of Individual Fairness in Graph Neural Networks He Zhang Xingliang Yuan Shirui Pan 39 11 0 30 Jan 2023
Fair Ranking with Noisy Protected Attributes Anay Mehrotra Nisheeth K. Vishnoi 23 16 0 30 Nov 2022
Differential Privacy has Bounded Impact on Fairness in Classification Paul Mangold Michaël Perrot A. Bellet Marc Tommasi 31 17 0 28 Oct 2022
Disparate Impact in Differential Privacy from Gradient Misalignment Maria S. Esipova Atiyeh Ashari Ghomi Yaqiao Luo Jesse C. Cresswell 29 25 0 15 Jun 2022
Differential Privacy and Fairness in Decisions and Learning Tasks: A Survey Ferdinando Fioretto Cuong Tran Pascal Van Hentenryck Keyu Zhu FaML 32 60 0 16 Feb 2022
Fair Sequential Selection Using Supervised Learning Models Mohammad Mahdi Khalili Xueru Zhang Mahed Abroshan FaML 36 20 0 26 Oct 2021
Fairness-Driven Private Collaborative Machine Learning Dana Pessach Tamir Tassa E. Shmueli FedML 33 7 0 29 Sep 2021
A Fairness Analysis on Private Aggregation of Teacher Ensembles Cuong Tran M. H. Dinh Kyle Beiter Ferdinando Fioretto 21 12 0 17 Sep 2021
Federated Learning Meets Fairness and Differential Privacy P. Manisha Sankarshan Damle Sujit Gujar FedML 32 21 0 23 Aug 2021
Balance is key: Private median splits yield high-utility random trees Shorya Consul Sinead Williamson 11 2 0 15 Jun 2020
Robust Optimization for Fairness with Noisy Protected Groups S. Wang Wenshuo Guo Harikrishna Narasimhan Andrew Cotter Maya R. Gupta Michael I. Jordan NoLa 27 118 0 21 Feb 2020