Average Individual Fairness: Algorithms, Generalization and Experiments

25 May 2019

Michael Kearns

Aaron Roth

Saeed Sharifi-Malvajerdi

FaML

FedML

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Papers citing "Average Individual Fairness: Algorithms, Generalization and Experiments"

48 / 48 papers shown

Title
Rethinking Fair Graph Neural Networks from Re-balancing Zhixun Li Yushun Dong Qiang Liu Jeffrey Xu Yu 31 7 0 16 Jul 2024
Enrolment-based personalisation for improving individual-level fairness in speech emotion recognition Andreas Triantafyllopoulos Björn Schuller 27 1 0 10 Jun 2024
Towards Explainability and Fairness in Swiss Judgement Prediction: Benchmarking on a Multilingual Dataset Santosh T.Y.S.S Nina Baumgartner Matthias Sturmer Matthias Grabmair Joel Niklaus ELM AILaw 31 6 0 26 Feb 2024
Certification of Distributional Individual Fairness Matthew Wicker Vihari Piratla Adrian Weller 19 1 0 20 Nov 2023
Toward Operationalizing Pipeline-aware ML Fairness: A Research Agenda for Developing Practical Guidelines and Tools Maximilian Schambach Rakshit Naidu Rayid Ghani Kit T. Rodolfa Daniel E. Ho Hoda Heidari FaML 35 14 0 29 Sep 2023
Monitoring Algorithmic Fairness under Partial Observations T. Henzinger Konstantin Kueffner Kaushik Mallik MLAU 25 2 0 01 Aug 2023
Algorithms, Incentives, and Democracy E. M. Penn John W. Patty FaML 24 2 0 05 Jul 2023
FFPDG: Fast, Fair and Private Data Generation Weijie Xu Jinjin Zhao Francis Iannacci Bo Wang 20 11 0 30 Jun 2023
FFB: A Fair Fairness Benchmark for In-Processing Group Fairness Methods Xiaotian Han Jianfeng Chi Yu Chen Qifan Wang Han Zhao Na Zou Xia Hu 44 25 0 15 Jun 2023
Monitoring Algorithmic Fairness T. Henzinger Mahyar Karimi Konstantin Kueffner Kaushik Mallik FaML 21 6 0 25 May 2023
ACROCPoLis: A Descriptive Framework for Making Sense of Fairness Andrea Aler Tubella Dimitri Coelho Mollo Adam Dahlgren Lindstrom Hannah Devinney Virginia Dignum ... Anna Jonsson T. Kampik Tom Lenaerts Julian Alfredo Mendez J. Nieves 17 8 0 19 Apr 2023
Achieving Counterfactual Fairness with Imperfect Structural Causal Model Tri Dung Duong Qian Li Guandong Xu 22 2 0 26 Mar 2023
From Utilitarian to Rawlsian Designs for Algorithmic Fairness Daniel E. Rigobon FaML 20 1 0 07 Feb 2023
Manifestations of Xenophobia in AI Systems Nenad Tomašev J. L. Maynard Iason Gabriel 24 9 0 15 Dec 2022
Learning Antidote Data to Individual Unfairness Peizhao Li Ethan Xia Hongfu Liu FedML FaML 17 9 0 29 Nov 2022
Fair and Optimal Classification via Post-Processing Ruicheng Xian Lang Yin Han Zhao FaML 16 30 0 03 Nov 2022
Systematic Evaluation of Predictive Fairness Xudong Han Aili Shen Trevor Cohn Timothy Baldwin Lea Frermann 26 7 0 17 Oct 2022
Omnipredictors for Constrained Optimization Lunjia Hu Inbal Livni-Navon Omer Reingold Chutong Yang 16 14 0 15 Sep 2022
Fairness in Forecasting of Observations of Linear Dynamical Systems Quan Zhou Jakub Mareˇcek Robert Shorten AI4TS 32 5 0 12 Sep 2022
Metric-Fair Classifier Derandomization Jimmy Wu Yatong Chen Yang Liu FaML 56 5 0 15 Jun 2022
What-is and How-to for Fairness in Machine Learning: A Survey, Reflection, and Perspective Zeyu Tang Jiji Zhang Kun Zhang FaML 25 26 0 08 Jun 2022
Metrizing Fairness Yves Rychener Bahar Taşkesen Daniel Kuhn FaML 36 4 0 30 May 2022
Optimising Equal Opportunity Fairness in Model Training Aili Shen Xudong Han Trevor Cohn Timothy Baldwin Lea Frermann FaML 21 28 0 05 May 2022
A Fair Empirical Risk Minimization with Generalized Entropy Young-Hwan Jin Jio Gim Tae-Jin Lee Young-Joo Suh FaML 16 1 0 24 Feb 2022
Learning fair representation with a parametric integral probability metric Dongha Kim Kunwoong Kim Insung Kong Ilsang Ohn Yongdai Kim FaML 17 16 0 07 Feb 2022
Learning Fair Node Representations with Graph Counterfactual Fairness Jing Ma Ruocheng Guo Mengting Wan Longqi Yang Aidong Zhang Jundong Li FaML 12 78 0 10 Jan 2022
Unified Group Fairness on Federated Learning Fengda Zhang Kun Kuang Yuxuan Liu Long Chen Chao-Xiang Wu Fei Wu Jiaxun Lu Yunfeng Shao Jun Xiao FedML 57 20 0 09 Nov 2021
A survey on datasets for fairness-aware machine learning Tai Le Quy Arjun Roy Vasileios Iosifidis Wenbin Zhang Eirini Ntoutsi FaML 11 240 0 01 Oct 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 25 42 0 07 Sep 2021
Subgroup Fairness in Two-Sided Markets Quan-Gen Zhou Jakub Mareˇcek Robert Shorten 17 2 0 04 Jun 2021
Pareto Efficient Fairness in Supervised Learning: From Extraction to Tracing Mohammad Mahdi Kamani R. Forsati J. Z. Wang M. Mahdavi FaML 11 11 0 04 Apr 2021
Individually Fair Gradient Boosting Alexander Vargo Fan Zhang Mikhail Yurochkin Yuekai Sun FaML FedML 16 15 0 31 Mar 2021
An Empirical Framework for Domain Generalization in Clinical Settings Haoran Zhang Natalie Dullerud Laleh Seyyed-Kalantari Q. Morris Shalmali Joshi Marzyeh Ghassemi OOD AI4CE 24 59 0 20 Mar 2021
Lexicographically Fair Learning: Algorithms and Generalization Emily Diana Wesley Gill Ira Globus-Harris Michael Kearns Aaron Roth Saeed Sharifi-Malvajerdi FedML FaML 65 9 0 16 Feb 2021
Removing biased data to improve fairness and accuracy Sahil Verma Michael Ernst René Just FaML 14 24 0 05 Feb 2021
Controllable Guarantees for Fair Outcomes via Contrastive Information Estimation Umang Gupta Aaron Ferber B. Dilkina Greg Ver Steeg 20 53 0 11 Jan 2021
Learning Fair Policies in Decentralized Cooperative Multi-Agent Reinforcement Learning Matthieu Zimmer Claire Glanois Umer Siddique Paul Weng OffRL 15 58 0 17 Dec 2020
No Subclass Left Behind: Fine-Grained Robustness in Coarse-Grained Classification Problems N. Sohoni Jared A. Dunnmon Geoffrey Angus Albert Gu Christopher Ré 18 240 0 25 Nov 2020
Beyond Individual and Group Fairness Pranjal Awasthi Corinna Cortes Yishay Mansour M. Mohri FaML 18 22 0 21 Aug 2020
Moment Multicalibration for Uncertainty Estimation Christopher Jung Changhwa Lee Mallesh M. Pai Aaron Roth R. Vohra UQCV 10 64 0 18 Aug 2020
Ensuring Fairness Beyond the Training Data Debmalya Mandal Samuel Deng Suman Jana Jeannette M. Wing Daniel J. Hsu FaML OOD 11 58 0 12 Jul 2020
Individual Calibration with Randomized Forecasting Shengjia Zhao Tengyu Ma Stefano Ermon 6 57 0 18 Jun 2020
Fairness in Forecasting and Learning Linear Dynamical Systems Quan-Gen Zhou Jakub Mareˇcek Robert Shorten AI4TS 24 7 0 12 Jun 2020
A Notion of Individual Fairness for Clustering Matthäus Kleindessner Pranjal Awasthi Jamie Morgenstern FaML 17 30 0 08 Jun 2020
On the Fairness of Randomized Trials for Recommendation with Heterogeneous Demographics and Beyond Zifeng Wang Xi Chen Rui Wen Shao-Lun Huang 6 1 0 25 Jan 2020
Kernel Dependence Regularizers and Gaussian Processes with Applications to Algorithmic Fairness Zhu Li Adrián Pérez-Suay Gustau Camps-Valls Dino Sejdinovic FaML 10 21 0 11 Nov 2019
Preference-Informed Fairness Michael P. Kim Aleksandra Korolova G. Rothblum G. Yona FaML 15 41 0 03 Apr 2019
Fair prediction with disparate impact: A study of bias in recidivism prediction instruments Alexandra Chouldechova FaML 207 2,082 0 24 Oct 2016