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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Title
All of the Fairness for Edge Prediction with Optimal Transport Charlotte Laclau I. Redko Manvi Choudhary C. Largeron FaML 22 42 0 30 Oct 2020
One-vs.-One Mitigation of Intersectional Bias: A General Method to Extend Fairness-Aware Binary Classification Kenji Kobayashi Yuri Nakao FaML 30 8 0 26 Oct 2020
Coping with Label Shift via Distributionally Robust Optimisation J.N. Zhang A. Menon Andreas Veit Srinadh Bhojanapalli Sanjiv Kumar S. Sra OOD 24 70 0 23 Oct 2020
Can I Trust My Fairness Metric? Assessing Fairness with Unlabeled Data and Bayesian Inference Disi Ji Padhraic Smyth M. Steyvers 44 45 0 19 Oct 2020
Equitable Allocation of Healthcare Resources with Fair Cox Models Kamrun Naher Keya Rashidul Islam Shimei Pan I. Stockwell James R. Foulds 14 9 0 14 Oct 2020
On the Fairness of Causal Algorithmic Recourse Julius von Kügelgen Amir-Hossein Karimi Umang Bhatt Isabel Valera Adrian Weller Bernhard Schölkopf FaML 80 83 0 13 Oct 2020
To be Robust or to be Fair: Towards Fairness in Adversarial Training Han Xu Xiaorui Liu Yaxin Li Anil K. Jain Jiliang Tang 17 179 0 13 Oct 2020
FaiR-N: Fair and Robust Neural Networks for Structured Data Shubham Sharma Alan H. Gee D. Paydarfar Joydeep Ghosh 26 18 0 13 Oct 2020
Bridging Machine Learning and Mechanism Design towards Algorithmic Fairness Jessie Finocchiaro R. Maio F. Monachou Gourab K. Patro Manish Raghavan Ana-Andreea Stoica Stratis Tsirtsis FaML 26 57 0 12 Oct 2020
Robust Fairness under Covariate Shift Ashkan Rezaei Anqi Liu Omid Memarrast Brian Ziebart TTA OOD 14 84 0 11 Oct 2020
Fairness-aware Agnostic Federated Learning Wei Du Depeng Xu Xintao Wu Yangqiu Song FedML 21 128 0 10 Oct 2020
Metrics and methods for a systematic comparison of fairness-aware machine learning algorithms Gareth Jones James M. Hickey Pietro G. Di Stefano C. Dhanjal Laura C. Stoddart V. Vasileiou FaML 33 21 0 08 Oct 2020
Assessing Classifier Fairness with Collider Bias Zhenlong Xu Ziqi Xu Jixue Liu Debo Cheng Jiuyong Li Lin Liu Adelaide Canada Ziqi Xu Zhenlong Xu contributed equally to this paper CML FaML 20 4 0 08 Oct 2020
Fairness in Machine Learning: A Survey Simon Caton C. Haas FaML 37 620 0 04 Oct 2020
MARS-Gym: A Gym framework to model, train, and evaluate Recommender Systems for Marketplaces Marlesson R. O. Santana Luckeciano C. Melo Fernando H. F. Camargo Bruno Brandão Anderson Soares Renan M. Oliveira Sandor Caetano OffRL 16 15 0 30 Sep 2020
Towards a Measure of Individual Fairness for Deep Learning Krystal Maughan Joseph P. Near TDI FaML 23 5 0 28 Sep 2020
Differentially Private and Fair Deep Learning: A Lagrangian Dual Approach Cuong Tran Ferdinando Fioretto Pascal Van Hentenryck FedML 39 78 0 26 Sep 2020
Fairness in Semi-supervised Learning: Unlabeled Data Help to Reduce Discrimination Tao Zhang Tianqing Zhu Jing Li Mengde Han Wanlei Zhou Philip S. Yu FaML 39 49 0 25 Sep 2020
Rank-Based Multi-task Learning for Fair Regression Chen Zhao Feng Chen FaML 16 31 0 23 Sep 2020
Fairness Constraints in Semi-supervised Learning Tao Zhang Tianqing Zhu Mengde Han Jing Li Wanlei Zhou Philip S. Yu FaML 22 7 0 14 Sep 2020
Addressing Fairness in Classification with a Model-Agnostic Multi-Objective Algorithm Kirtan Padh Diego Antognini Emma Lejal Glaude Boi Faltings C. Musat FaML 24 30 0 09 Sep 2020
On the Identification of Fair Auditors to Evaluate Recommender Systems based on a Novel Non-Comparative Fairness Notion Mukund Telukunta Venkata Sriram Siddhardh Nadendla FaML 16 0 0 09 Sep 2020
Say No to the Discrimination: Learning Fair Graph Neural Networks with Limited Sensitive Attribute Information Enyan Dai Suhang Wang FaML 16 241 0 03 Sep 2020
The Fairness-Accuracy Pareto Front Susan Wei Marc Niethammer FaML 51 33 0 25 Aug 2020
Aligning AI With Shared Human Values Dan Hendrycks Collin Burns Steven Basart Andrew Critch Jingkai Li D. Song Jacob Steinhardt 63 524 0 05 Aug 2020
Accuracy and Fairness Trade-offs in Machine Learning: A Stochastic Multi-Objective Approach Suyun Liu Luis Nunes Vicente FaML 29 68 0 03 Aug 2020
Fairness-Aware Online Personalization G. R. Lal S. Geyik K. Kenthapadi FaML 16 3 0 30 Jul 2020
A minimax framework for quantifying risk-fairness trade-off in regression Evgenii Chzhen Nicolas Schreuder FaML 36 32 0 28 Jul 2020
A Distributionally Robust Approach to Fair Classification Bahar Taşkesen Viet Anh Nguyen Daniel Kuhn Jose H. Blanchet FaML 28 61 0 18 Jul 2020
Ensuring Fairness Beyond the Training Data Debmalya Mandal Samuel Deng Suman Jana Jeannette M. Wing Daniel J. Hsu FaML OOD 27 58 0 12 Jul 2020
Algorithmic Fairness in Education René F. Kizilcec Hansol Lee FaML 38 120 0 10 Jul 2020
Transparency Tools for Fairness in AI (Luskin) Mingliang Chen Aria Shahverdi S. I. G. Anderson Se Yong Park Justin Zhang Dana Dachman-Soled Kristin E. Lauter Min Wu 9 2 0 09 Jul 2020
Tilted Empirical Risk Minimization Tian Li Ahmad Beirami Maziar Sanjabi Virginia Smith 22 128 0 02 Jul 2020
Machine learning fairness notions: Bridging the gap with real-world applications K. Makhlouf Sami Zhioua C. Palamidessi FaML 16 53 0 30 Jun 2020
SenSeI: Sensitive Set Invariance for Enforcing Individual Fairness Mikhail Yurochkin Yuekai Sun FaML 25 49 0 25 Jun 2020
On Fair Selection in the Presence of Implicit Variance V. Emelianov Nicolas Gast Krishna P. Gummadi P. Loiseau 6 37 0 24 Jun 2020
Fairness without Demographics through Adversarially Reweighted Learning Preethi Lahoti Alex Beutel Jilin Chen Kang Lee Flavien Prost Nithum Thain Xuezhi Wang Ed H. Chi FaML 30 331 0 23 Jun 2020
Fair Performance Metric Elicitation Gaurush Hiranandani Harikrishna Narasimhan Oluwasanmi Koyejo 32 18 0 23 Jun 2020
How fair can we go in machine learning? Assessing the boundaries of fairness in decision trees Ana Valdivia Javier Sánchez-Monedero J. Casillas FaML 43 46 0 22 Jun 2020
Achieving Fairness via Post-Processing in Web-Scale Recommender Systems Preetam Nandy Cyrus DiCiccio Divya Venugopalan Heloise Logan Kinjal Basu N. Karoui FaML 29 30 0 19 Jun 2020
Towards Threshold Invariant Fair Classification Mingliang Chen Min Wu FaML 19 13 0 18 Jun 2020
Algorithmic Decision Making with Conditional Fairness Renzhe Xu Peng Cui Kun Kuang Bo Li Linjun Zhou Zheyan Shen Wei Cui FaML 23 36 0 18 Jun 2020
LimeOut: An Ensemble Approach To Improve Process Fairness Vaishnavi Bhargava Miguel Couceiro A. Napoli FaML 29 20 0 17 Jun 2020
On Adversarial Bias and the Robustness of Fair Machine Learning Hong Chang Ta Duy Nguyen S. K. Murakonda Ehsan Kazemi Reza Shokri FaML OOD FedML 16 51 0 15 Jun 2020
Towards Model-Agnostic Post-Hoc Adjustment for Balancing Ranking Fairness and Algorithm Utility Sen Cui Weishen Pan Changshui Zhang Fei Wang 22 13 0 15 Jun 2020
Fair Regression with Wasserstein Barycenters Evgenii Chzhen Christophe Denis Mohamed Hebiri L. Oneto Massimiliano Pontil 35 101 0 12 Jun 2020
Fair Classification with Noisy Protected Attributes: A Framework with Provable Guarantees L. E. Celis Lingxiao Huang Vijay Keswani Nisheeth K. Vishnoi FaML 25 9 0 08 Jun 2020
Meta Clustering for Collaborative Learning Chenglong Ye R. Ghanadan Jie Ding 36 4 0 29 May 2020
Review of Mathematical frameworks for Fairness in Machine Learning E. del Barrio Paula Gordaliza Jean-Michel Loubes FaML FedML 15 40 0 26 May 2020
Fair Classification via Unconstrained Optimization Ibrahim M. Alabdulmohsin FaML 20 6 0 21 May 2020