FRAPPE: A Group Fairness Framework for Post-Processing Everything

5 December 2023

Papers citing "FRAPPE: A Group Fairness Framework for Post-Processing Everything"

9 / 9 papers shown

Title
Multi-Output Distributional Fairness via Post-Processing Gang Li Qihang Lin Ayush Ghosh Tianbao Yang 47 0 0 31 Aug 2024
Fairness Reprogramming Guanhua Zhang Yihua Zhang Yang Zhang Wenqi Fan Qing Li Sijia Liu Shiyu Chang AAML 78 38 0 21 Sep 2022
Fairness via In-Processing in the Over-parameterized Regime: A Cautionary Tale A. Veldanda Ivan Brugere Jiahao Chen Sanghamitra Dutta Alan Mishler S. Garg 22 7 0 29 Jun 2022
Learning Fair Classifiers with Partially Annotated Group Labels Sangwon Jung Sanghyuk Chun Taesup Moon 60 46 0 29 Nov 2021
Fairness without Imputation: A Decision Tree Approach for Fair Prediction with Missing Values Haewon Jeong Hao Wang Flavio du Pin Calmon FaML 49 33 0 21 Sep 2021
Evaluating Fairness of Machine Learning Models Under Uncertain and Incomplete Information Pranjal Awasthi Alex Beutel Matthaeus Kleindessner Jamie Morgenstern Xuezhi Wang FaML 54 55 0 16 Feb 2021
A Survey on Bias and Fairness in Machine Learning Ninareh Mehrabi Fred Morstatter N. Saxena Kristina Lerman Aram Galstyan SyDa FaML 294 4,187 0 23 Aug 2019
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 192 739 0 13 Dec 2018
Learning Adversarially Fair and Transferable Representations David Madras Elliot Creager T. Pitassi R. Zemel FaML 210 669 0 17 Feb 2018