Technical Challenges for Training Fair Neural Networks

12 February 2021

Papers citing "Technical Challenges for Training Fair Neural Networks"

8 / 8 papers shown

Title
Provable Optimization for Adversarial Fair Self-supervised Contrastive Learning Qi Qi Quanqi Hu Qihang Lin Tianbao Yang 37 1 0 09 Jun 2024
Model Agnostic Sample Reweighting for Out-of-Distribution Learning Xiao Zhou Yong Lin Renjie Pi Weizhong Zhang Renzhe Xu Peng Cui Tong Zhang OODD 39 60 0 24 Jan 2023
Malign Overfitting: Interpolation Can Provably Preclude Invariance Yoav Wald G. Yona Uri Shalit Y. Carmon 17 5 0 28 Nov 2022
AUC Maximization in the Era of Big Data and AI: A Survey Tianbao Yang Yiming Ying 33 179 0 28 Mar 2022
Deep AUC Maximization for Medical Image Classification: Challenges and Opportunities Tianbao Yang 30 3 0 01 Nov 2021
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 192 742 0 13 Dec 2018
Learning Adversarially Fair and Transferable Representations David Madras Elliot Creager T. Pitassi R. Zemel FaML 233 674 0 17 Feb 2018
Fair prediction with disparate impact: A study of bias in recidivism prediction instruments Alexandra Chouldechova FaML 207 2,084 0 24 Oct 2016