Fairness Beyond Disparate Treatment & Disparate Impact: Learning Classification without Disparate Mistreatment

26 October 2016

Muhammad Bilal Zafar

Isabel Valera

Manuel Gomez Rodriguez

Krishna P. Gummadi

FaML

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Papers citing "Fairness Beyond Disparate Treatment & Disparate Impact: Learning Classification without Disparate Mistreatment"

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FairNeuron: Improving Deep Neural Network Fairness with Adversary Games on Selective Neurons Xuanqi Gao Juan Zhai Shiqing Ma Chao Shen Yufei Chen Qianqian Wang 34 37 0 06 Apr 2022
Semi-FairVAE: Semi-supervised Fair Representation Learning with Adversarial Variational Autoencoder Chuhan Wu Fangzhao Wu Tao Qi Yongfeng Huang DRL 19 3 0 01 Apr 2022
Repairing Group-Level Errors for DNNs Using Weighted Regularization Ziyuan Zhong Yuchi Tian Conor J. Sweeney Vicente Ordonez Baishakhi Ray 24 0 0 24 Mar 2022
Fair Federated Learning via Bounded Group Loss Shengyuan Hu Zhiwei Steven Wu Virginia Smith FaML FedML 29 14 0 18 Mar 2022
Distraction is All You Need for Fairness Mehdi Yazdani-Jahromi Amirarsalan Rajabi Ali Khodabandeh Yalabadi Aida Tayebi O. Garibay 13 2 0 15 Mar 2022
Fairness-aware Adversarial Perturbation Towards Bias Mitigation for Deployed Deep Models Peng Kuang Xiaowei Dong Henry Xue Zhifei Zhang Weifeng Chiu Tao Wei Kui Ren AAML 33 71 0 03 Mar 2022
Fast Feature Selection with Fairness Constraints Francesco Quinzan Rajiv Khanna Moshik Hershcovitch S. Cohen Daniel Waddington Tobias Friedrich Michael W. Mahoney 16 3 0 28 Feb 2022
A Fair Empirical Risk Minimization with Generalized Entropy Young-Hwan Jin Jio Gim Tae-Jin Lee Young-Joo Suh FaML 22 1 0 24 Feb 2022
Attainability and Optimality: The Equalized Odds Fairness Revisited Zeyu Tang Kun Zhang FaML 23 11 0 24 Feb 2022
Bayes-Optimal Classifiers under Group Fairness Xianli Zeng Yan Sun Guang Cheng FaML 21 23 0 20 Feb 2022
Human-Algorithm Collaboration: Achieving Complementarity and Avoiding Unfairness Kate Donahue Alexandra Chouldechova K. Kenthapadi FaML FedML 54 50 0 17 Feb 2022
Prediction Sensitivity: Continual Audit of Counterfactual Fairness in Deployed Classifiers Krystal Maughan Ivoline C. Ngong Joseph P. Near 22 2 0 09 Feb 2022
Fair Interpretable Representation Learning with Correction Vectors Mattia Cerrato A. Coronel Marius Köppel A. Segner Roberto Esposito Stefan Kramer FaML 19 5 0 07 Feb 2022
FORML: Learning to Reweight Data for Fairness Bobby Yan Skyler Seto N. Apostoloff FaML 31 11 0 03 Feb 2022
Proportional Fairness in Federated Learning Guojun Zhang Saber Malekmohammadi Xi Chen Yaoliang Yu FedML 30 24 0 03 Feb 2022
Diagnosing failures of fairness transfer across distribution shift in real-world medical settings Jessica Schrouff Natalie Harris Oluwasanmi Koyejo Ibrahim M. Alabdulmohsin Eva Schnider ... Vivek Natarajan Alan Karthikesalingam Katherine A. Heller Silvia Chiappa Alexander DÁmour OOD 71 53 0 02 Feb 2022
Fairness of Machine Learning Algorithms in Demography I. Emmanuel E. Mitrofanova FaML 16 0 0 02 Feb 2022
Adaptive Sampling Strategies to Construct Equitable Training Datasets William Cai R. Encarnación Bobbie Chern S. Corbett-Davies Miranda Bogen Stevie Bergman Sharad Goel 89 30 0 31 Jan 2022
Understanding Why Generalized Reweighting Does Not Improve Over ERM Runtian Zhai Chen Dan Zico Kolter Pradeep Ravikumar OOD 44 27 0 28 Jan 2022
Fairness Implications of Encoding Protected Categorical Attributes Carlos Mougan J. Álvarez Salvatore Ruggieri Steffen Staab FaML 29 14 0 27 Jan 2022
Promises and Challenges of Causality for Ethical Machine Learning Aida Rahmattalabi Alice Xiang FaML CML 128 8 0 26 Jan 2022
An Algorithmic Framework for Bias Bounties Ira Globus-Harris Michael Kearns Aaron Roth FedML 102 24 0 25 Jan 2022
Are Commercial Face Detection Models as Biased as Academic Models? Samuel Dooley George Z. Wei Tom Goldstein John P. Dickerson CVBM 48 4 0 25 Jan 2022
Fair Interpretable Learning via Correction Vectors Mattia Cerrato Marius Köppel A. Segner Stefan Kramer FaML CML 16 1 0 17 Jan 2022
Fair Group-Shared Representations with Normalizing Flows Mattia Cerrato M. Koppel A. Segner Stefan Kramer FedML FaML OOD 11 5 0 17 Jan 2022
FairIF: Boosting Fairness in Deep Learning via Influence Functions with Validation Set Sensitive Attributes Haonan Wang Ziwei Wu Jingrui He 24 12 0 15 Jan 2022
Learning Fair Node Representations with Graph Counterfactual Fairness Jing Ma Ruocheng Guo Mengting Wan Longqi Yang Aidong Zhang Jundong Li FaML 22 79 0 10 Jan 2022
The Effect of Model Compression on Fairness in Facial Expression Recognition Samuil Stoychev Hatice Gunes CVBM 30 19 0 05 Jan 2022
AutoBalance: Optimized Loss Functions for Imbalanced Data Mingchen Li Xuechen Zhang Christos Thrampoulidis Jiasi Chen Samet Oymak 24 67 0 04 Jan 2022
Parity-based Cumulative Fairness-aware Boosting Vasileios Iosifidis Arjun Roy Eirini Ntoutsi FaML 20 4 0 04 Jan 2022
Fair Data Representation for Machine Learning at the Pareto Frontier Shizhou Xu Thomas Strohmer 14 5 0 02 Jan 2022
Data Collection and Quality Challenges in Deep Learning: A Data-Centric AI Perspective Steven Euijong Whang Yuji Roh Hwanjun Song Jae-Gil Lee 29 327 0 13 Dec 2021
Fairness for Robust Learning to Rank Omid Memarrast Ashkan Rezaei Rizal Fathony Brian Ziebart FaML 15 11 0 12 Dec 2021
On Fair Selection in the Presence of Implicit and Differential Variance V. Emelianov Nicolas Gast Krishna P. Gummadi P. Loiseau 32 21 0 10 Dec 2021
Assessing Fairness in the Presence of Missing Data Yiliang Zhang Q. Long FaML 33 35 0 07 Dec 2021
Fairness for AUC via Feature Augmentation H. Fong Vineet Kumar Anay Mehrotra Nisheeth K. Vishnoi 36 10 0 24 Nov 2021
CONFAIR: Configurable and Interpretable Algorithmic Fairness Ankit Kulshrestha Ilya Safro FaML 22 2 0 17 Nov 2021
Interpretable and Fair Boolean Rule Sets via Column Generation Connor Lawless S. Dash Oktay Gunluk Dennis L. Wei FaML 21 12 0 16 Nov 2021
Proposing an Interactive Audit Pipeline for Visual Privacy Research Jasmine DeHart Chenguang Xu Lisa Egede Christan Earl Grant HAI 18 3 0 07 Nov 2021
Increasing Fairness in Predictions Using Bias Parity Score Based Loss Function Regularization Bhanu Jain Manfred Huber R. Elmasri 25 1 0 05 Nov 2021
Modeling Techniques for Machine Learning Fairness: A Survey Mingyang Wan Daochen Zha Ninghao Liu Na Zou SyDa FaML 37 36 0 04 Nov 2021
Towards Fairness-Aware Federated Learning Yuxin Shi Han Yu Cyril Leung FedML 21 79 0 02 Nov 2021
Unintended Selection: Persistent Qualification Rate Disparities and Interventions Reilly P. Raab Yang Liu 28 24 0 01 Nov 2021
Improving Fairness via Federated Learning Yuchen Zeng Hongxu Chen Kangwook Lee FedML 24 61 0 29 Oct 2021
Fairer LP-based Online Allocation via Analytic Center Guanting Chen Xiaocheng Li Yinyu Ye FaML 23 8 0 27 Oct 2021
Sample Selection for Fair and Robust Training Yuji Roh Kangwook Lee Steven Euijong Whang Changho Suh 21 62 0 27 Oct 2021
Fairness in Missing Data Imputation Yiliang Zhang Q. Long 38 12 0 22 Oct 2021
Does Data Repair Lead to Fair Models? Curating Contextually Fair Data To Reduce Model Bias Sharat Agarwal Sumanyu Muku Saket Anand Chetan Arora 14 11 0 20 Oct 2021
Comparing Human and Machine Bias in Face Recognition Samuel Dooley Ryan Downing George Z. Wei N. Shankar Bradon Thymes ... Olufemi Obiwumi Valeriia Cherepanova Micah Goldblum John P. Dickerson Tom Goldstein CVBM 115 12 0 15 Oct 2021
Multi-Objective Few-shot Learning for Fair Classification Ishani Mondal Procheta Sen Debasis Ganguly FaML 18 4 0 05 Oct 2021