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

ArXiv PDF HTML

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

50 / 572 papers shown

Title
Algorithm Fairness in AI for Medicine and Healthcare Richard J. Chen Tiffany Y. Chen Jana Lipkova Judy J. Wang Drew F. K. Williamson Ming Y. Lu S. Sahai Faisal Mahmood FaML 75 45 0 01 Oct 2021
A survey on datasets for fairness-aware machine learning Tai Le Quy Arjun Roy Vasileios Iosifidis Wenbin Zhang Eirini Ntoutsi FaML 13 243 0 01 Oct 2021
Fairness-Driven Private Collaborative Machine Learning Dana Pessach Tamir Tassa E. Shmueli FedML 33 7 0 29 Sep 2021
Fairness guarantee in multi-class classification Christophe Denis Romuald Elie Mohamed Hebiri Franccois Hu FaML 57 48 0 28 Sep 2021
Fast and Efficient MMD-based Fair PCA via Optimization over Stiefel Manifold Junghyun Lee Gwangsun Kim Matt Olfat M. Hasegawa-Johnson Chang D. Yoo 28 16 0 23 Sep 2021
Toward a Fairness-Aware Scoring System for Algorithmic Decision-Making Yi Yang Ying Nian Wu Mei Li Xiangyu Chang Yong Tan FaML 23 0 0 21 Sep 2021
Enforcing fairness in private federated learning via the modified method of differential multipliers Borja Rodríguez Gálvez Filip Granqvist Rogier van Dalen M. Seigel FedML 48 53 0 17 Sep 2021
FedFair: Training Fair Models In Cross-Silo Federated Learning Lingyang Chu Lanjun Wang Yanjie Dong J. Pei Zirui Zhou Yong Zhang FedML 58 40 0 13 Sep 2021
Amazon SageMaker Clarify: Machine Learning Bias Detection and Explainability in the Cloud Michaela Hardt Xiaoguang Chen Xiaoyi Cheng Michele Donini J. Gelman ... Muhammad Bilal Zafar Sanjiv Ranjan Das Kevin Haas Tyler Hill K. Kenthapadi ELM FaML 36 42 0 07 Sep 2021
FADE: FAir Double Ensemble Learning for Observable and Counterfactual Outcomes Alan Mishler Edward H. Kennedy FaML 35 23 0 01 Sep 2021
Towards Out-Of-Distribution Generalization: A Survey Jiashuo Liu Zheyan Shen Yue He Xingxuan Zhang Renzhe Xu Han Yu Peng Cui CML OOD 69 520 0 31 Aug 2021
Robustness Disparities in Commercial Face Detection Samuel Dooley Tom Goldstein John P. Dickerson CVBM 35 13 0 27 Aug 2021
Understanding and Mitigating Annotation Bias in Facial Expression Recognition Yunliang Chen Jungseock Joo CVBM 36 80 0 19 Aug 2021
The Sharpe predictor for fairness in machine learning Suyun Liu Luis Nunes Vicente 43 3 0 13 Aug 2021
Learning Bias-Invariant Representation by Cross-Sample Mutual Information Minimization Wei-wei Zhu Haitian Zheng Haofu Liao Weijian Li Jiebo Luo 35 43 0 11 Aug 2021
Explaining Algorithmic Fairness Through Fairness-Aware Causal Path Decomposition Weishen Pan Sen Cui Jiang Bian Changshui Zhang Fei Wang CML FaML 27 35 0 11 Aug 2021
GIFAIR-FL: A Framework for Group and Individual Fairness in Federated Learning Xubo Yue Maher Nouiehed Raed Al Kontar FedML 40 37 0 05 Aug 2021
Reducing Unintended Bias of ML Models on Tabular and Textual Data Guilherme Alves M. Amblard Fabien Bernier Miguel Couceiro A. Napoli FaML 27 15 0 05 Aug 2021
Fair Representation Learning using Interpolation Enabled Disentanglement Akshita Jha B. Vinzamuri Chandan K. Reddy FedML 45 3 0 31 Jul 2021
FairBalance: How to Achieve Equalized Odds With Data Pre-processing Zhe Yu Joymallya Chakraborty Tim Menzies FaML 49 3 0 17 Jul 2021
Fairness in Ranking under Uncertainty Ashudeep Singh David Kempe Thorsten Joachims 38 49 0 14 Jul 2021
Fairness-aware Summarization for Justified Decision-Making Moniba Keymanesh T. Berger-Wolf Micha Elsner Srinivasan Parthasarathy 22 5 0 13 Jul 2021
Trustworthy AI: A Computational Perspective Haochen Liu Yiqi Wang Wenqi Fan Xiaorui Liu Yaxin Li Shaili Jain Yunhao Liu Anil K. Jain Jiliang Tang FaML 104 197 0 12 Jul 2021
Bias-Tolerant Fair Classification Yixuan Zhang Feng Zhou Zhidong Li Yang Wang Fang Chen 37 3 0 07 Jul 2021
Fair Decision Rules for Binary Classification Connor Lawless Oktay Gunluk FaML 26 6 0 03 Jul 2021
FLEA: Provably Robust Fair Multisource Learning from Unreliable Training Data Eugenia Iofinova Nikola Konstantinov Christoph H. Lampert FaML 36 0 0 22 Jun 2021
Characterizing the risk of fairwashing Ulrich Aïvodji Hiromi Arai Sébastien Gambs Satoshi Hara 23 27 0 14 Jun 2021
User Acceptance of Gender Stereotypes in Automated Career Recommendations Clarice Wang Kathryn Wang Andrew Bian Rashidul Islam Kamrun Naher Keya James Foulde Shimei Pan FaML 33 7 0 13 Jun 2021
DORO: Distributional and Outlier Robust Optimization Runtian Zhai Chen Dan J. Zico Kolter Pradeep Ravikumar 33 60 0 11 Jun 2021
Fair Classification with Adversarial Perturbations L. E. Celis Anay Mehrotra Nisheeth K. Vishnoi FaML 29 32 0 10 Jun 2021
A Near-Optimal Algorithm for Debiasing Trained Machine Learning Models Ibrahim M. Alabdulmohsin Mario Lucic 27 22 0 06 Jun 2021
Addressing the Long-term Impact of ML Decisions via Policy Regret David Lindner Hoda Heidari Andreas Krause OffRL 25 6 0 02 Jun 2021
Testing Group Fairness via Optimal Transport Projections Nian Si Karthyek Murthy Jose H. Blanchet Viet Anh Nguyen 33 29 0 02 Jun 2021
Information Theoretic Measures for Fairness-aware Feature Selection S. Khodadadian M. Nafea AmirEmad Ghassami Negar Kiyavash 27 8 0 01 Jun 2021
A Clarification of the Nuances in the Fairness Metrics Landscape Alessandro Castelnovo Riccardo Crupi Greta Greco D. Regoli Ilaria Giuseppina Penco A. Cosentini FaML 20 183 0 01 Jun 2021
Using Pareto Simulated Annealing to Address Algorithmic Bias in Machine Learning William Blanzeisky Padraig Cunningham FaML 44 7 0 31 May 2021
Personalized Counterfactual Fairness in Recommendation Yunqi Li Hanxiong Chen Shuyuan Xu Yingqiang Ge Yongfeng Zhang FaML OffRL 29 142 0 20 May 2021
How Costly is Noise? Data and Disparities in Consumer Credit Laura Blattner Scott Nelson 10 42 0 17 May 2021
Fairly Private Through Group Tagging and Relation Impact Poushali Sengupta Subhankar Mishra 28 0 0 15 May 2021
Bias, Fairness, and Accountability with AI and ML Algorithms Neng-Zhi Zhou Zach Zhang V. Nair Harsh Singhal Jie Chen Agus Sudjianto FaML 21 9 0 13 May 2021
An Empirical Comparison of Bias Reduction Methods on Real-World Problems in High-Stakes Policy Settings Hemank Lamba Kit T. Rodolfa Rayid Ghani OffRL 44 17 0 13 May 2021
Accounting for Model Uncertainty in Algorithmic Discrimination Junaid Ali Adish Singla Krishna P. Gummadi FaML 31 21 0 10 May 2021
A Novel Estimator of Mutual Information for Learning to Disentangle Textual Representations Pierre Colombo Chloé Clavel Pablo Piantanida AAML DRL 26 50 0 06 May 2021
Algorithms are not neutral: Bias in collaborative filtering Catherine Stinson FaML 25 28 0 03 May 2021
User-oriented Fairness in Recommendation Yunqi Li H. Chen Zuohui Fu Yingqiang Ge Yongfeng Zhang FaML 106 230 0 21 Apr 2021
TFROM: A Two-sided Fairness-Aware Recommendation Model for Both Customers and Providers Yao Wu Jian Cao Guandong Xu Yudong Tan FaML 27 85 0 19 Apr 2021
Fair Representation Learning for Heterogeneous Information Networks Ziqian Zeng Rashidul Islam Kamrun Naher Keya James R. Foulds Yangqiu Song Shimei Pan 32 40 0 18 Apr 2021
Implementing Fair Regression In The Real World Boris Ruf Marcin Detyniecki 28 1 0 09 Apr 2021
Explainability-aided Domain Generalization for Image Classification Robin M. Schmidt FAtt OOD 27 1 0 05 Apr 2021
Pareto Efficient Fairness in Supervised Learning: From Extraction to Tracing Mohammad Mahdi Kamani R. Forsati Jianmin Wang M. Mahdavi FaML 13 11 0 04 Apr 2021