Towards Fair Classifiers Without Sensitive Attributes: Exploring Biases in Related Features

29 April 2021

Papers citing "Towards Fair Classifiers Without Sensitive Attributes: Exploring Biases in Related Features"

6 / 6 papers shown

Title
MAPPING: Debiasing Graph Neural Networks for Fair Node Classification with Limited Sensitive Information Leakage Ying Song Balaji Palanisamy 80 0 0 28 Jan 2025
Fairness Risks for Group-conditionally Missing Demographics Kaiqi Jiang Wenzhe Fan Mao Li Xinhua Zhang 105 0 0 20 Feb 2024
Trading-off price for data quality to achieve fair online allocation M. Molina Nicolas Gast P. Loiseau Vianney Perchet 24 4 0 23 Jun 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
Improving Fairness in Graph Neural Networks via Mitigating Sensitive Attribute Leakage Yu-Chiang Frank Wang Yuying Zhao Yushun Dong Huiyuan Chen Jundong Li Tyler Derr 25 80 0 07 Jun 2022
A Survey on Bias and Fairness in Machine Learning Ninareh Mehrabi Fred Morstatter N. Saxena Kristina Lerman Aram Galstyan SyDa FaML 335 4,223 0 23 Aug 2019