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Preventing Fairness Gerrymandering: Auditing and Learning for Subgroup Fairness

14 November 2017

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

50 / 448 papers shown

Title
Fairness in Matching under Uncertainty Siddartha Devic David Kempe Vatsal Sharan Aleksandra Korolova FaML 78 6 0 08 Feb 2023
Linking convolutional kernel size to generalization bias in face analysis CNNs Hao Liang J. O. Caro Vikram Maheshri Ankit B. Patel Guha Balakrishnan CVBM CML 77 0 0 07 Feb 2023
From Utilitarian to Rawlsian Designs for Algorithmic Fairness Daniel E. Rigobon FaML 47 1 0 07 Feb 2023
To Be Forgotten or To Be Fair: Unveiling Fairness Implications of Machine Unlearning Methods Dawen Zhang Shidong Pan Thong Hoang Zhenchang Xing Mark Staples Xiwei Xu Lina Yao Qinghua Lu Liming Zhu MU 67 21 0 07 Feb 2023
Bitrate-Constrained DRO: Beyond Worst Case Robustness To Unknown Group Shifts Amrith Rajagopal Setlur D. Dennis Benjamin Eysenbach Aditi Raghunathan Chelsea Finn Virginia Smith Sergey Levine OOD 76 11 0 06 Feb 2023
Constrained Online Two-stage Stochastic Optimization: Near Optimal Algorithms via Adversarial Learning Jiashuo Jiang 86 0 0 02 Feb 2023
Aleatoric and Epistemic Discrimination: Fundamental Limits of Fairness Interventions Hao Wang Luxi He Rui Gao Flavio du Pin Calmon 46 10 0 27 Jan 2023
From Pseudorandomness to Multi-Group Fairness and Back Cynthia Dwork Daniel Lee Huijia Lin Pranay Tankala FaML 98 11 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 49 1 0 26 Dec 2022
Stochastic Methods for AUC Optimization subject to AUC-based Fairness Constraints Yao Yao Qihang Lin Tianbao Yang FaML 98 7 0 23 Dec 2022
An Efficient Framework for Monitoring Subgroup Performance of Machine Learning Systems Huong Ha 75 0 0 16 Dec 2022
Manifestations of Xenophobia in AI Systems Nenad Tomašev J. L. Maynard Iason Gabriel 102 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 83 3 0 14 Dec 2022
A Unifying Theory of Distance from Calibration Jarosław Błasiok Parikshit Gopalan Lunjia Hu Preetum Nakkiran 102 41 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 92 89 0 25 Nov 2022
Subgroup Robustness Grows On Trees: An Empirical Baseline Investigation Josh Gardner Zoran Popovic Ludwig Schmidt OOD 107 23 0 23 Nov 2022
Comparative Learning: A Sample Complexity Theory for Two Hypothesis Classes Lunjia Hu Charlotte Peale 55 8 0 16 Nov 2022
Using Open-Ended Stressor Responses to Predict Depressive Symptoms across Demographics Carlos Alejandro Aguirre Mark Dredze Philip Resnik 51 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 62 2 0 11 Nov 2022
Can Querying for Bias Leak Protected Attributes? Achieving Privacy With Smooth Sensitivity Faisal Hamman Jiahao Chen Sanghamitra Dutta 75 9 0 03 Nov 2022
Fair and Optimal Classification via Post-Processing Ruicheng Xian Lang Yin Han Zhao FaML 145 32 0 03 Nov 2022
Private and Reliable Neural Network Inference Nikola Jovanović Marc Fischer Samuel Steffen Martin Vechev 75 15 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 117 39 0 19 Oct 2022
Group Fairness in Prediction-Based Decision Making: From Moral Assessment to Implementation Joachim Baumann Christoph Heitz 60 8 0 19 Oct 2022
Stochastic Differentially Private and Fair Learning Andrew Lowy Devansh Gupta Meisam Razaviyayn FaML FedML 61 14 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 66 0 0 11 Oct 2022
Making Decisions under Outcome Performativity Michael P. Kim Juan C. Perdomo 99 21 0 04 Oct 2022
Batch Multivalid Conformal Prediction Christopher Jung Georgy Noarov Ramya Ramalingam Aaron Roth 263 53 0 30 Sep 2022
Fair admission risk prediction with proportional multicalibration William La Cava Elle Lett Guangya Wan 102 8 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 188 21 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 81 3 0 22 Sep 2022
Towards Auditing Unsupervised Learning Algorithms and Human Processes For Fairness Ian Davidson S. S. Ravi FaML 62 1 0 20 Sep 2022
Algorithmic decision making methods for fair credit scoring Darie Moldovan FaML 85 7 0 16 Sep 2022
Multicalibrated Regression for Downstream Fairness Ira Globus-Harris Varun Gupta Christopher Jung Michael Kearns Jamie Morgenstern Aaron Roth FaML 124 12 0 15 Sep 2022
Adaptive Fairness Improvement Based on Causality Analysis Mengdi Zhang Jun Sun 57 36 0 15 Sep 2022
Fair Inference for Discrete Latent Variable Models Rashidul Islam Shimei Pan James R. Foulds FaML 93 1 0 15 Sep 2022
Exploiting Fairness to Enhance Sensitive Attributes Reconstruction Julien Ferry Ulrich Aïvodji Sébastien Gambs Marie-José Huguet Mohamed Siala AAML 70 14 0 02 Sep 2022
Fair mapping Sébastien Gambs Rosin Claude Ngueveu 84 0 0 01 Sep 2022
Debiasing Word Embeddings with Nonlinear Geometry Lu Cheng Nayoung Kim Huan Liu 69 5 0 29 Aug 2022
TESTSGD: Interpretable Testing of Neural Networks Against Subtle Group Discrimination Mengdi Zhang Jun Sun Jingyi Wang Bing-Jie Sun 69 15 0 24 Aug 2022
Ex-Ante Assessment of Discrimination in Dataset Jonathan Vasquez Verdugo Xavier Gitiaux Huzefa Rangwala 71 0 0 16 Aug 2022
Locating disparities in machine learning Moritz von Zahn O. Hinz Stefan Feuerriegel 67 5 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 101 21 0 02 Aug 2022
Towards Fairness-Aware Multi-Objective Optimization Guo-Ding Yu Lianbo Ma W. Du WenLi Du Yaochu Jin FaML 95 7 0 22 Jul 2022
MANI-Rank: Multiple Attribute and Intersectional Group Fairness for Consensus Ranking Kathleen Cachel Elke A. Rundensteiner Lane Harrison FaML 56 12 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 61 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 113 177 0 14 Jul 2022
Bottlenecks CLUB: Unifying Information-Theoretic Trade-offs Among Complexity, Leakage, and Utility Behrooz Razeghi Flavio du Pin Calmon Deniz Gunduz Svyatoslav Voloshynovskiy 58 16 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 81 10 0 24 Jun 2022
FairGrad: Fairness Aware Gradient Descent Gaurav Maheshwari Michaël Perrot FaML 104 12 0 22 Jun 2022