Papers citing 'Fair Learning with Private Demographic Data'

Title
Quantifying Query Fairness Under Unawareness Thomas Jaenich Alejandro Moreo Alessandro Fabris Graham McDonald Andrea Esuli Iadh Ounis Fabrizio Sebastiani 117 0 0 04 Jun 2025
Private Rate-Constrained Optimization with Applications to Fair Learning Mohammad Yaghini Tudor Cebere Michael Menart A. Bellet Nicolas Papernot 120 0 0 28 May 2025
Discrimination-free Insurance Pricing with Privatized Sensitive Attributes Tianhe Zhang Suhan Liu Peng Shi FaML 153 0 0 16 Apr 2025
PFGuard: A Generative Framework with Privacy and Fairness Safeguards Soyeon Kim Yuji Roh Geon Heo Steven Euijong Whang 167 0 0 03 Oct 2024
Differentially Private Data Release on Graphs: Inefficiencies and Unfairness Ferdinando Fioretto Diptangshu Sen Juba Ziani 91 1 0 08 Aug 2024
Linkage on Security, Privacy and Fairness in Federated Learning: New Balances and New Perspectives Linlin Wang Tianqing Zhu Wanlei Zhou Philip S. Yu 95 3 0 16 Jun 2024
A Systematic and Formal Study of the Impact of Local Differential Privacy on Fairness: Preliminary Results K. Makhlouf Tamara Stefanovic Héber H. Arcolezi C. Palamidessi 100 4 0 23 May 2024
Differentially Private Post-Processing for Fair Regression Ruicheng Xian Qiaobo Li Gautam Kamath Han Zhao 133 4 0 07 May 2024
Differentially Private Fair Binary Classifications Hrad Ghoukasian S. Asoodeh FaML 124 3 0 23 Feb 2024
Fairness Risks for Group-conditionally Missing Demographics Kaiqi Jiang Wenzhe Fan Mao Li Xinhua Zhang 271 0 0 20 Feb 2024
Regulation Games for Trustworthy Machine Learning Mohammad Yaghini Patty Liu Franziska Boenisch Nicolas Papernot FaML 73 3 0 05 Feb 2024
SoK: Taming the Triangle -- On the Interplays between Fairness, Interpretability and Privacy in Machine Learning Julien Ferry Ulrich Aïvodji Sébastien Gambs Marie-José Huguet Mohamed Siala FaML 104 7 0 22 Dec 2023
On the Impact of Multi-dimensional Local Differential Privacy on Fairness K. Makhlouf Héber H. Arcolezi Sami Zhioua G. B. Brahim C. Palamidessi 120 8 0 07 Dec 2023
Toward the Tradeoffs between Privacy, Fairness and Utility in Federated Learning Kangkang Sun Xiaojin Zhang Xi Lin Gaolei Li Jing Wang Jianhua Li 98 5 0 30 Nov 2023
Estimating and Implementing Conventional Fairness Metrics With Probabilistic Protected Features Hadi Elzayn Emily Black Patrick Vossler Nathanael Jo Jacob Goldin Daniel E. Ho 79 6 0 02 Oct 2023
Unlocking Accuracy and Fairness in Differentially Private Image Classification Leonard Berrada Soham De J. Shen Jamie Hayes Robert Stanforth David Stutz Pushmeet Kohli Samuel L. Smith Borja Balle 100 16 0 21 Aug 2023
When Fair Classification Meets Noisy Protected Attributes Avijit Ghosh Pablo Kvitca Chris L. Wilson FaML 83 10 0 06 Jul 2023
Privacy and Fairness in Federated Learning: on the Perspective of Trade-off Huiqiang Chen Tianqing Zhu Tao Zhang Wanlei Zhou Philip S. Yu FedML 104 60 0 25 Jun 2023
Sampling Individually-Fair Rankings that are Always Group Fair Sruthi Gorantla Anay Mehrotra Amit Deshpande Anand Louis FedML FaML 88 4 0 21 Jun 2023
Survey of Trustworthy AI: A Meta Decision of AI Caesar Wu Yuan-Fang Li Pascal Bouvry 142 3 0 01 Jun 2023
FairDP: Certified Fairness with Differential Privacy K. Tran Ferdinando Fioretto Issa M. Khalil My T. Thai Nhathai Phan 138 0 0 25 May 2023
On the Fairness Impacts of Private Ensembles Models Cuong Tran Ferdinando Fioretto 126 6 0 19 May 2023
(Local) Differential Privacy has NO Disparate Impact on Fairness Héber H. Arcolezi K. Makhlouf C. Palamidessi 135 7 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 136 10 0 17 Feb 2023
Group Fairness with Uncertainty in Sensitive Attributes Abhin Shah Maohao Shen J. Jon Ryu Subhro Das P. Sattigeri Yuheng Bu G. Wornell FaML 96 5 0 16 Feb 2023
Hyper-parameter Tuning for Fair Classification without Sensitive Attribute Access A. Veldanda Shubham Sharma Sanghamitra Dutta Alan Mishler S. Garg 125 6 0 02 Feb 2023
Unraveling Privacy Risks of Individual Fairness in Graph Neural Networks He Zhang Lizhen Qu Shirui Pan 164 17 0 30 Jan 2023
Fair Ranking with Noisy Protected Attributes Anay Mehrotra Nisheeth K. Vishnoi 109 20 0 30 Nov 2022
Differential Privacy has Bounded Impact on Fairness in Classification Paul Mangold Michaël Perrot A. Bellet Marc Tommasi 133 21 0 28 Oct 2022
Stochastic Differentially Private and Fair Learning Andrew Lowy Devansh Gupta Meisam Razaviyayn FaML FedML 110 15 0 17 Oct 2022
Outlier-Robust Group Inference via Gradient Space Clustering Yuchen Zeng Kristjan Greenewald Kangwook Lee Justin Solomon Mikhail Yurochkin 75 2 0 13 Oct 2022
When Fairness Meets Privacy: Fair Classification with Semi-Private Sensitive Attributes Canyu Chen Yueqing Liang Xiongxiao Xu Shangyu Xie A. Kundu Ali Payani Yuan Hong Kai Shu 74 7 0 18 Jul 2022
Disparate Impact in Differential Privacy from Gradient Misalignment Maria S. Esipova Atiyeh Ashari Ghomi Yaqiao Luo Jesse C. Cresswell 159 34 0 15 Jun 2022
SF-PATE: Scalable, Fair, and Private Aggregation of Teacher Ensembles Cuong Tran Keyu Zhu Ferdinando Fioretto Pascal Van Hentenryck 95 12 0 11 Apr 2022
Differential Privacy and Fairness in Decisions and Learning Tasks: A Survey Ferdinando Fioretto Cuong Tran Pascal Van Hentenryck Keyu Zhu FaML 105 67 0 16 Feb 2022
Fair Sequential Selection Using Supervised Learning Models Mohammad Mahdi Khalili Xueru Zhang Mahed Abroshan FaML 82 22 0 26 Oct 2021
Fairness-Driven Private Collaborative Machine Learning Dana Pessach Tamir Tassa E. Shmueli FedML 86 7 0 29 Sep 2021
A Sociotechnical View of Algorithmic Fairness Mateusz Dolata Stefan Feuerriegel Gerhard Schwabe FaML 99 105 0 27 Sep 2021
A Fairness Analysis on Private Aggregation of Teacher Ensembles Cuong Tran M. H. Dinh Kyle Beiter Ferdinando Fioretto 102 12 0 17 Sep 2021
Federated Learning Meets Fairness and Differential Privacy P. Manisha Sankarshan Damle Sujit Gujar FedML 105 21 0 23 Aug 2021
Statistical Guarantees for Fairness Aware Plug-In Algorithms Drona Khurana S. Ravichandran Sparsh Jain N. Edakunni FaML 129 0 0 27 Jul 2021
Differentially Empirical Risk Minimization under the Fairness Lens Cuong Tran My H. Dinh Ferdinando Fioretto 107 48 0 04 Jun 2021
Fairly Private Through Group Tagging and Relation Impact Poushali Sengupta Subhankar Mishra 88 1 0 15 May 2021
A Stochastic Optimization Framework for Fair Risk Minimization Andrew Lowy Sina Baharlouei Rakesh Pavan Meisam Razaviyayn Ahmad Beirami FaML 163 23 0 24 Feb 2021
Fairness-Aware PAC Learning from Corrupted Data Nikola Konstantinov Christoph H. Lampert 122 21 0 11 Feb 2021
Improving Fairness and Privacy in Selection Problems Mohammad Mahdi Khalili Xueru Zhang Mahed Abroshan Somayeh Sojoudi 166 28 0 07 Dec 2020
Differentially Private and Fair Deep Learning: A Lagrangian Dual Approach Cuong Tran Ferdinando Fioretto Pascal Van Hentenryck FedML 112 83 0 26 Sep 2020
Balance is key: Private median splits yield high-utility random trees Shorya Consul Sinead Williamson 125 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 98 122 0 21 Feb 2020