Blind Justice: Fairness with Encrypted Sensitive Attributes

8 June 2018

Papers citing "Blind Justice: Fairness with Encrypted Sensitive Attributes"

21 / 21 papers shown

Title
FairJob: A Real-World Dataset for Fairness in Online Systems Mariia Vladimirova Federico Pavone Eustache Diemert 54 1 0 03 Jul 2024
Laminator: Verifiable ML Property Cards using Hardware-assisted Attestations Vasisht Duddu Oskari Jarvinen Lachlan J. Gunn Nirmal Asokan 74 1 0 25 Jun 2024
A Sequentially Fair Mechanism for Multiple Sensitive Attributes Franccois Hu Philipp Ratz Arthur Charpentier FaML 20 6 0 12 Sep 2023
Mitigating Cross-client GANs-based Attack in Federated Learning Hong Huang Xinyu Lei Tao Xiang AAML 60 1 0 25 Jul 2023
Can Querying for Bias Leak Protected Attributes? Achieving Privacy With Smooth Sensitivity Faisal Hamman Jiahao Chen Sanghamitra Dutta 25 9 0 03 Nov 2022
Differential Privacy has Bounded Impact on Fairness in Classification Paul Mangold Michaël Perrot A. Bellet Marc Tommasi 41 17 0 28 Oct 2022
Federated Graph-based Networks with Shared Embedding Tianyi Yu Pei-Ci Lai Fei Teng FedML 34 3 0 03 Oct 2022
"You Can't Fix What You Can't Measure": Privately Measuring Demographic Performance Disparities in Federated Learning Marc Juárez Aleksandra Korolova FedML 32 9 0 24 Jun 2022
Federated learning: Applications, challenges and future directions Subrato Bharati Hossain Mondal Prajoy Podder V. B. Surya Prasath FedML 41 53 0 18 May 2022
Demographic-Reliant Algorithmic Fairness: Characterizing the Risks of Demographic Data Collection in the Pursuit of Fairness Mckane Andrus Sarah Villeneuve FaML 32 50 0 18 Apr 2022
Fairness-Driven Private Collaborative Machine Learning Dana Pessach Tamir Tassa E. Shmueli FedML 33 7 0 29 Sep 2021
MPC-Friendly Commitments for Publicly Verifiable Covert Security Nitin Agrawal James Bell Adria Gascon Matt J. Kusner 28 4 0 15 Sep 2021
Fairness without the sensitive attribute via Causal Variational Autoencoder Vincent Grari Sylvain Lamprier Marcin Detyniecki 24 27 0 10 Sep 2021
Multiaccurate Proxies for Downstream Fairness Emily Diana Wesley Gill Michael Kearns K. Kenthapadi Aaron Roth Saeed Sharifi-Malvajerdi 35 21 0 09 Jul 2021
"What We Can't Measure, We Can't Understand": Challenges to Demographic Data Procurement in the Pursuit of Fairness Mckane Andrus Elena Spitzer Jeffrey Brown Alice Xiang 32 126 0 30 Oct 2020
An Overview of Federated Deep Learning Privacy Attacks and Defensive Strategies David Enthoven Zaid Al-Ars FedML 60 50 0 01 Apr 2020
Fair Learning with Private Demographic Data Hussein Mozannar Mesrob I. Ohannessian Nathan Srebro 35 73 0 26 Feb 2020
A Distributed Fair Machine Learning Framework with Private Demographic Data Protection Hui Hu Yijun Liu Zhen Wang Chao Lan FaML FedML 46 25 0 17 Sep 2019
QUOTIENT: Two-Party Secure Neural Network Training and Prediction Nitin Agrawal Ali Shahin Shamsabadi Matt J. Kusner Adria Gascon 30 212 0 08 Jul 2019
Fair and Unbiased Algorithmic Decision Making: Current State and Future Challenges Songül Tolan FaML 24 31 0 15 Jan 2019
Differentially Private Fair Learning Matthew Jagielski Michael Kearns Jieming Mao Alina Oprea Aaron Roth Saeed Sharifi-Malvajerdi Jonathan R. Ullman FaML FedML 30 147 0 06 Dec 2018