Preventing Fairness Gerrymandering: Auditing and Learning for Subgroup Fairness

14 November 2017

Papers citing "Preventing Fairness Gerrymandering: Auditing and Learning for Subgroup Fairness"

50 / 443 papers shown

Title
Aleatoric and Epistemic Discrimination: Fundamental Limits of Fairness Interventions Hao Wang Luxi He Rui Gao Flavio du Pin Calmon 21 9 0 27 Jan 2023
From Pseudorandomness to Multi-Group Fairness and Back Cynthia Dwork Daniel Lee Huijia Lin Pranay Tankala FaML 38 9 0 21 Jan 2023
Bias Mitigation Framework for Intersectional Subgroups in Neural Networks Narine Kokhlikyan B. Alsallakh Fulton Wang Vivek Miglani Oliver Aobo Yang David Adkins 30 1 0 26 Dec 2022
Stochastic Methods for AUC Optimization subject to AUC-based Fairness Constraints Yao Yao Qihang Lin Tianbao Yang FaML 39 6 0 23 Dec 2022
An Efficient Framework for Monitoring Subgroup Performance of Machine Learning Systems Huong Ha 19 0 0 16 Dec 2022
Manifestations of Xenophobia in AI Systems Nenad Tomašev J. L. Maynard Iason Gabriel 24 9 0 15 Dec 2022
Tensions Between the Proxies of Human Values in AI Teresa Datta D. Nissani Max Cembalest Akash Khanna Haley Massa John P. Dickerson 39 2 0 14 Dec 2022
A Unifying Theory of Distance from Calibration Jarosław Błasiok Parikshit Gopalan Lunjia Hu Preetum Nakkiran 31 33 0 30 Nov 2022
Picking on the Same Person: Does Algorithmic Monoculture lead to Outcome Homogenization? Rishi Bommasani Kathleen A. Creel Ananya Kumar Dan Jurafsky Percy Liang 30 78 0 25 Nov 2022
Subgroup Robustness Grows On Trees: An Empirical Baseline Investigation Josh Gardner Zoran Popovic Ludwig Schmidt OOD 42 22 0 23 Nov 2022
Comparative Learning: A Sample Complexity Theory for Two Hypothesis Classes Lunjia Hu Charlotte Peale 43 6 0 16 Nov 2022
Using Open-Ended Stressor Responses to Predict Depressive Symptoms across Demographics Carlos Alejandro Aguirre Mark Dredze Philip Resnik 27 0 0 15 Nov 2022
Practical Approaches for Fair Learning with Multitype and Multivariate Sensitive Attributes Tennison Liu Alex J. Chan B. V. Breugel M. Schaar FaML 25 2 0 11 Nov 2022
Can Querying for Bias Leak Protected Attributes? Achieving Privacy With Smooth Sensitivity Faisal Hamman Jiahao Chen Sanghamitra Dutta 25 9 0 03 Nov 2022
Fair and Optimal Classification via Post-Processing Ruicheng Xian Lang Yin Han Zhao FaML 28 30 0 03 Nov 2022
Private and Reliable Neural Network Inference Nikola Jovanović Marc Fischer Samuel Steffen Martin Vechev 27 14 0 27 Oct 2022
On Learning Fairness and Accuracy on Multiple Subgroups Changjian Shui Gezheng Xu Qi Chen Jiaqi Li Charles Ling Tal Arbel Boyu Wang Christian Gagné 51 37 0 19 Oct 2022
Group Fairness in Prediction-Based Decision Making: From Moral Assessment to Implementation Joachim Baumann Christoph Heitz 31 8 0 19 Oct 2022
Stochastic Differentially Private and Fair Learning Andrew Lowy Devansh Gupta Meisam Razaviyayn FaML FedML 21 13 0 17 Oct 2022
Navigating Ensemble Configurations for Algorithmic Fairness Michael Feffer Martin Hirzel Samuel C. Hoffman Kiran Kate Parikshit Ram Avraham Shinnar FedML FaML 24 0 0 11 Oct 2022
Making Decisions under Outcome Performativity Michael P. Kim Juan C. Perdomo 51 19 0 04 Oct 2022
Batch Multivalid Conformal Prediction Christopher Jung Georgy Noarov Ramya Ramalingam Aaron Roth 75 50 0 30 Sep 2022
Fair admission risk prediction with proportional multicalibration William La Cava Elle Lett Guangya Wan 42 7 0 29 Sep 2022
Addressing Fairness Issues in Deep Learning-Based Medical Image Analysis: A Systematic Review Zikang Xu Jun Li Yongshuo Zong Han Li Qingsong Yao S. Kevin Zhou 54 15 0 27 Sep 2022
In Differential Privacy, There is Truth: On Vote Leakage in Ensemble Private Learning Jiaqi Wang R. Schuster Ilia Shumailov David Lie Nicolas Papernot FedML 35 3 0 22 Sep 2022
Towards Auditing Unsupervised Learning Algorithms and Human Processes For Fairness Ian Davidson S. S. Ravi FaML 38 1 0 20 Sep 2022
Algorithmic decision making methods for fair credit scoring Darie Moldovan FaML 35 7 0 16 Sep 2022
Multicalibrated Regression for Downstream Fairness Ira Globus-Harris Varun Gupta Christopher Jung Michael Kearns Jamie Morgenstern Aaron Roth FaML 60 11 0 15 Sep 2022
Adaptive Fairness Improvement Based on Causality Analysis Mengdi Zhang Jun Sun 24 31 0 15 Sep 2022
Fair Inference for Discrete Latent Variable Models Rashidul Islam Shimei Pan James R. Foulds FaML 53 1 0 15 Sep 2022
Exploiting Fairness to Enhance Sensitive Attributes Reconstruction Julien Ferry Ulrich Aïvodji Sébastien Gambs Marie-José Huguet Mohamed Siala AAML 42 14 0 02 Sep 2022
Fair mapping Sébastien Gambs Rosin Claude Ngueveu 42 0 0 01 Sep 2022
Debiasing Word Embeddings with Nonlinear Geometry Lu Cheng Nayoung Kim Huan Liu 24 5 0 29 Aug 2022
TESTSGD: Interpretable Testing of Neural Networks Against Subtle Group Discrimination Mengdi Zhang Jun Sun Jingyi Wang Bing-Jie Sun 21 14 0 24 Aug 2022
Ex-Ante Assessment of Discrimination in Dataset Jonathan Vasquez Verdugo Xavier Gitiaux Huzefa Rangwala 40 0 0 16 Aug 2022
Locating disparities in machine learning Moritz von Zahn O. Hinz Stefan Feuerriegel 27 4 0 13 Aug 2022
Mitigating Biases in Student Performance Prediction via Attention-Based Personalized Federated Learning Yun-Wei Chu Seyyedali Hosseinalipour Elizabeth Tenorio Laura Cruz K. Douglas Andrew Lan Christopher G. Brinton FedML AI4Ed 25 21 0 02 Aug 2022
Towards Fairness-Aware Multi-Objective Optimization Guo-Ding Yu Lianbo Ma W. Du WenLi Du Yaochu Jin FaML 37 7 0 22 Jul 2022
MANI-Rank: Multiple Attribute and Intersectional Group Fairness for Consensus Ranking Kathleen Cachel Elke A. Rundensteiner Lane Harrison FaML 21 11 0 20 Jul 2022
When Fairness Meets Privacy: Fair Classification with Semi-Private Sensitive Attributes Canyu Chen Yueqing Liang Xiongxiao Xu Shangyu Xie A. Kundu Ali Payani Yuan Hong Kai Shu 24 6 0 18 Jul 2022
Bias Mitigation for Machine Learning Classifiers: A Comprehensive Survey Max Hort Zhenpeng Chen Jie M. Zhang Mark Harman Federica Sarro FaML AI4CE 38 162 0 14 Jul 2022
Bottlenecks CLUB: Unifying Information-Theoretic Trade-offs Among Complexity, Leakage, and Utility Behrooz Razeghi Flavio du Pin Calmon Deniz Gunduz Slava Voloshynovskiy 31 15 0 11 Jul 2022
"You Can't Fix What You Can't Measure": Privately Measuring Demographic Performance Disparities in Federated Learning Marc Juárez Aleksandra Korolova FedML 34 9 0 24 Jun 2022
FairGrad: Fairness Aware Gradient Descent Gaurav Maheshwari Michaël Perrot FaML 46 11 0 22 Jun 2022
Algorithmic Fairness and Vertical Equity: Income Fairness with IRS Tax Audit Models Emily Black Hadi Elzayn Alexandra Chouldechova Jacob Goldin Daniel E. Ho MLAU 30 25 0 20 Jun 2022
Respect as a Lens for the Design of AI Systems W. Seymour Max Van Kleek Reuben Binns Dave Murray-Rust FaML 19 6 0 15 Jun 2022
Bounding and Approximating Intersectional Fairness through Marginal Fairness M. Molina P. Loiseau 34 8 0 12 Jun 2022
What-is and How-to for Fairness in Machine Learning: A Survey, Reflection, and Perspective Zeyu Tang Jiji Zhang Kun Zhang FaML 38 26 0 08 Jun 2022
How unfair is private learning ? Amartya Sanyal Yaxian Hu Fanny Yang FaML FedML 35 22 0 08 Jun 2022
Fair Classification via Domain Adaptation: A Dual Adversarial Learning Approach Yueqing Liang Canyu Chen Tian Tian Kai Shu FaML 16 9 0 08 Jun 2022