Weak Proxies are Sufficient and Preferable for Fairness with Missing
Sensitive Attributes

Weak Proxies are Sufficient and Preferable for Fairness with Missing Sensitive Attributes

6 October 2022

Zhaowei Zhu

Papers citing "Weak Proxies are Sufficient and Preferable for Fairness with Missing Sensitive Attributes"

13 / 13 papers shown

Title
Constructing Fair Latent Space for Intersection of Fairness and Explainability Hyungjun Joo Hyeonggeun Han Sehwan Kim Sangwoo Hong Jungwoo Lee 29 0 0 23 Dec 2024
Alpha and Prejudice: Improving $α$ -sized Worst-case Fairness via Intrinsic Reweighting Jing Li Yinghua Yao Yuangang Pan Xuanqian Wang Ivor Tsang Xiuju Fu FaML 23 0 0 05 Nov 2024
Fairness Risks for Group-conditionally Missing Demographics Kaiqi Jiang Wenzhe Fan Mao Li Xinhua Zhang 67 0 0 20 Feb 2024
Distributionally Robust Post-hoc Classifiers under Prior Shifts Jiaheng Wei Harikrishna Narasimhan Ehsan Amid Wenjun Chu Yang Liu Abhishek Kumar OOD 35 16 0 16 Sep 2023
Hyper-parameter Tuning for Fair Classification without Sensitive Attribute Access A. Veldanda Ivan Brugere Sanghamitra Dutta Alan Mishler S. Garg 17 5 0 02 Feb 2023
Mitigating Neural Network Overconfidence with Logit Normalization Hongxin Wei Renchunzi Xie Hao-Ran Cheng Lei Feng Bo An Yixuan Li OODD 163 258 0 19 May 2022
Detecting Corrupted Labels Without Training a Model to Predict Zhaowei Zhu Zihao Dong Yang Liu NoLa 141 61 0 12 Oct 2021
The Rich Get Richer: Disparate Impact of Semi-Supervised Learning Zhaowei Zhu Tianyi Luo Yang Liu 148 39 0 12 Oct 2021
Evaluating Fairness of Machine Learning Models Under Uncertain and Incomplete Information Pranjal Awasthi Alex Beutel Matthaeus Kleindessner Jamie Morgenstern Xuezhi Wang FaML 49 55 0 16 Feb 2021
Combating noisy labels by agreement: A joint training method with co-regularization Hongxin Wei Lei Feng Xiangyu Chen Bo An NoLa 303 488 0 05 Mar 2020
Improving fairness in machine learning systems: What do industry practitioners need? Kenneth Holstein Jennifer Wortman Vaughan Hal Daumé Miroslav Dudík Hanna M. Wallach FaML HAI 192 730 0 13 Dec 2018
Learning Adversarially Fair and Transferable Representations David Madras Elliot Creager T. Pitassi R. Zemel FaML 208 663 0 17 Feb 2018
Fair prediction with disparate impact: A study of bias in recidivism prediction instruments Alexandra Chouldechova FaML 185 2,079 0 24 Oct 2016