The Fairness of Risk Scores Beyond Classification: Bipartite Ranking and the xAUC Metric

15 February 2019

Papers citing "The Fairness of Risk Scores Beyond Classification: Bipartite Ranking and the xAUC Metric"

16 / 16 papers shown

Title
Enforcing Fairness Where It Matters: An Approach Based on Difference-of-Convex Constraints Yutian He Yankun Huang Yao Yao Qihang Lin FaML 22 0 0 18 May 2025
Beyond Submodularity: A Unified Framework of Randomized Set Selection with Group Fairness Constraints Shaojie Tang Jing Yuan FaML 27 12 0 13 Apr 2023
Minimax AUC Fairness: Efficient Algorithm with Provable Convergence Zhenhuan Yang Yan Lok Ko Kush R. Varshney Yiming Ying FaML 33 17 0 22 Aug 2022
Disparate Censorship & Undertesting: A Source of Label Bias in Clinical Machine Learning Trenton Chang Michael Sjoding Jenna Wiens 26 11 0 01 Aug 2022
AUC Maximization in the Era of Big Data and AI: A Survey Tianbao Yang Yiming Ying 44 179 0 28 Mar 2022
Fairness for AUC via Feature Augmentation H. Fong Vineet Kumar Anay Mehrotra Nisheeth K. Vishnoi 34 10 0 24 Nov 2021
Deep AUC Maximization for Medical Image Classification: Challenges and Opportunities Tianbao Yang 30 3 0 01 Nov 2021
Consider the Alternatives: Navigating Fairness-Accuracy Tradeoffs via Disqualification G. Rothblum G. Yona FaML 27 1 0 02 Oct 2021
A comparison of approaches to improve worst-case predictive model performance over patient subpopulations Stephen R. Pfohl Haoran Zhang Yizhe Xu Agata Foryciarz Marzyeh Ghassemi N. Shah OOD 29 22 0 27 Aug 2021
Addressing Algorithmic Disparity and Performance Inconsistency in Federated Learning Sen Cui Weishen Pan Jian Liang Changshui Zhang Fei Wang FedML 17 84 0 19 Aug 2021
Fairness in Ranking under Uncertainty Ashudeep Singh David Kempe Thorsten Joachims 33 49 0 14 Jul 2021
Deep ROC Analysis and AUC as Balanced Average Accuracy to Improve Model Selection, Understanding and Interpretation André M. Carrington D. Manuel Paul Fieguth T. Ramsay V. Osmani ... S. Hawken M. McInnes Olivia Magwood Yusuf Sheikh Andreas Holzinger 25 129 0 21 Mar 2021
An Empirical Characterization of Fair Machine Learning For Clinical Risk Prediction Stephen R. Pfohl Agata Foryciarz N. Shah FaML 33 108 0 20 Jul 2020
Pairwise Fairness for Ranking and Regression Harikrishna Narasimhan Andrew Cotter Maya R. Gupta S. Wang 22 112 0 12 Jun 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 195 742 0 13 Dec 2018
Fair prediction with disparate impact: A study of bias in recidivism prediction instruments Alexandra Chouldechova FaML 207 2,091 0 24 Oct 2016