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Fairness in machine learning has attracted increasing attention in recent years.
Achieving ethics and fairness in hiring: Going beyond the law
G Stoney Alder and Joseph Gilbert · 2006
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Perceptions of overall fairness: are effects on job performance moderated by leader-member exchange?
Jeff Johnson, Donald M Truxillo, Berrin Erdogan, Talya N Bauer, and Leslie Hammer · 2009
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Optimal transport: old and new
Cédric Villani et al · 2009
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Covariate shift by kernel mean matching
Arthur Gretton, Alex Smola, Jiayuan Huang, Marcel Schmittfull, Karsten Borgwardt, and Bernhard Schölkopf · 2009
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Rectified linear units improve restricted boltzmann machines
Vinod Nair and Geoffrey E Hinton · 2010
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Principal component analysis
Hervé Abdi and Lynne J Williams · 2010
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Fairness-aware classifier with prejudice remover regularizer
Toshihiro Kamishima, Shotaro Akaho, Hideki Asoh, and Jun Sakuma · 2012
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Fairness in education: The italian university before and after the reform
Paolo Brunori, Vito Peragine, and Laura Serlenga · 2012
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Fairness in education–a normative analysis of oecd policy documents
Steinar Bøyum · 2014
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The variational fair autoencoder
Christos Louizos, Kevin Swersky, Yujia Li, Max Welling, and Richard Zemel · 2015
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Equality of opportunity in supervised learning
Moritz Hardt, Eric Price, and Nati Srebro · 2016
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UCI machine learning repository, 2017
Dheeru Dua and Casey Graff · 2017
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Data decisions and theoretical implications when adversarially learning fair representations
Alex Beutel, Jilin Chen, Zhe Zhao, and Ed H Chi · 2017
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Learning to pivot with adversarial networks
Gilles Louppe, Michael Kagan, and Kyle Cranmer · 2017
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Counterfactual fairness
Matt J Kusner, Joshua Loftus, Chris Russell, and Ricardo Silva · 2017
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A short-term intervention for long-term fairness in the labor market
Lily Hu and Yiling Chen · 2018
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Fairness definitions explained
Sahil Verma and Julia Rubin · 2018
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Benchmarking neural network robustness to common corruptions and perturbations
Dan Hendrycks and Thomas Dietterich · 2019
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Why machine learning may lead to unfairness: Evidence from risk assessment for juvenile justice in catalonia
Songül Tolan, Marius Miron, Emilia Gómez, and Carlos Castillo · 2019
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Measuring robustness to natural distribution shifts in image classification
Rohan Taori, Achal Dave, Vaishaal Shankar, Nicholas Carlini, Benjamin Recht, and Ludwig Schmidt · 2020
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Improving robustness against common corruptions by covariate shift adaptation
Steffen Schneider, Evgenia Rusak, Luisa Eck, Oliver Bringmann, Wieland Brendel, and Matthias Bethge · 2020
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Fairness in machine learning for healthcare
Muhammad Aurangzeb Ahmad, Arpit Patel, Carly Eckert, Vikas Kumar, and Ankur Teredesai · 2020
Cited alongside, same era.
Sharpness-aware minimization for efficiently improving generalization
Pierre Foret, Ariel Kleiner, Hossein Mobahi, and Behnam Neyshabur · 2020
Cited alongside, same era.
Fair mixup: Fairness via interpolation
Ching-Yao Chuang and Youssef Mroueh · 2020
Cited alongside, same era.
Machine learning in healthcare: Fairness, issues, and challenges
Margrét Vilborg Bjarnadóttir and David Anderson · 2020
Cited alongside, same era.
On dyadic fairness: Exploring and mitigating bias in graph connections
Peizhao Li, Yifei Wang, Han Zhao, Pengyu Hong, and Hongfu Liu · 2020
Cited alongside, same era.
Training individually fair ml models with sensitive subspace robustness
Assessing the fairness of ai systems: Ai practitioners’ processes, challenges, and needs for support
Michael Madaio, Lisa Egede, Hariharan Subramonyam, Jennifer Wortman Vaughan, and Hanna Wallach · 2022
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Efficient resource allocation with fairness constraints in restless multi-armed bandits
Dexun Li and Pradeep Varakantham · 2022
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Fmp: Toward fair graph message passing against topology bias
Zhimeng Jiang, Xiaotian Han, Chao Fan, Zirui Liu, Na Zou, Ali Mostafavi, and Xia Hu · 2022
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Enabling fairness in healthcare through machine learning
Thomas Grote and Geoff Keeling · 2022
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Algorithmic fairness in education
René F Kizilcec and Hansol Lee · 2022
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Mikhail Yurochkin, Amanda Bower, and Yuekai Sun · 2020
Cited alongside, same era.
Two simple ways to learn individual fairness metrics from data
Debarghya Mukherjee, Mikhail Yurochkin, Moulinath Banerjee, and Yuekai Sun · 2020
Cited alongside, same era.
Inform: Individual fairness on graph mining
Jian Kang, Jingrui He, Ross Maciejewski, and Hanghang Tong · 2020
Cited alongside, same era.
The many faces of robustness: A critical analysis of out-of-distribution generalization
Dan Hendrycks, Steven Basart, Norman Mu, Saurav Kadavath, Frank Wang, Evan Dorundo, Rahul Desai, Tyler Zhu, Samyak Parajuli, Mike Guo, et al · 2021
Cited alongside, same era.
Fair classification with adversarial perturbations
L Elisa Celis, Anay Mehrotra, and Nisheeth Vishnoi · 2021
Cited alongside, same era.
Retiring adult: New datasets for fair machine learning
Frances Ding, Moritz Hardt, John Miller, and Ludwig Schmidt · 2021
Cited alongside, same era.
Robust fairness under covariate shift
Ashkan Rezaei, Anqi Liu, Omid Memarrast, and Brian D Ziebart · 2021
Cited alongside, same era.
Gaurush Hiranandani, Jatin Mathur, Harikrishna Narasimhan, and Oluwasanmi Koyejo · 2022
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Generalized demographic parity for group fairness
Zhimeng Jiang, Xiaotian Han, Chao Fan, Fan Yang, Ali Mostafavi, and Xia Hu · 2022
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Domain adaptation meets individual fairness. and they get along
Debarghya Mukherjee, Felix Petersen, Mikhail Yurochkin, and Yuekai Sun · 2022
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Individual fairness in feature-based pricing for monopoly markets
Shantanu Das, Swapnil Dhamal, Ganesh Ghalme, Shweta Jain, and Sujit Gujar · 2022
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Counterfactual fairness with partially known causal graph
Aoqi Zuo, Susan Wei, Tongliang Liu, Bo Han, Kun Zhang, and Mingming Gong · 2022
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Jessica Schrouff, Natalie Harris, Oluwasanmi Koyejo, Ibrahim Alabdulmohsin, Eva Schnider, Krista Opsahl-Ong, Alex Brown, Subhrajit Roy, Diana Mincu, Christina Chen, et al · 2022
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Fairness guarantees under demographic shift
Stephen Giguere, Blossom Metevier, Bruno Castro da Silva, Yuriy Brun, Philip Thomas, and Scott Niekum · 2022
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Efficient sharpness-aware minimization for improved training of neural networks
Jiawei Du, Hanshu Yan, Jiashi Feng, Joey Tianyi Zhou, Liangli Zhen, Rick Siow Mong Goh, and Vincent YF Tan · 2022
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Towards understanding sharpness-aware minimization
Maksym Andriushchenko and Nicolas Flammarion · 2022
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Predicting out-of-distribution error with the projection norm
Yaodong Yu, Zitong Yang, Alexander Wei, Yi Ma, and Jacob Steinhardt · 2022
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Retiring Δ \Delta DP: New distribution-level metrics for demographic parity
Xiaotian Han, Zhimeng Jiang, Hongye Jin, Zirui Liu, Na Zou, Qifan Wang, and Xia Hu · 2023
Closest in time.
Data-centric artificial intelligence: A survey
Daochen Zha, Zaid Pervaiz Bhat, Kwei-Herng Lai, Fan Yang, Zhimeng Jiang, Shaochen Zhong, and Xia Hu · 2023
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Fair graph distillation
Qizhang Feng, Zhimeng Jiang, Ruiquan Li, Yicheng Wang, Na Zou, Jiang Bian, and Xia Hu · 2023
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Coda: Temporal domain generalization via concept drift simulator
Chia-Yuan Chang, Yu-Neng Chuang, Zhimeng Jiang, Kwei-Herng Lai, Anxiao Jiang, and Na Zou · 2023
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Consistent range approximation for fair predictive modeling
Jiongli Zhu, Sainyam Galhotra, Nazanin Sabri, and Babak Salimi · 2023
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Predicting out-of-distribution error with confidence optimal transport
Yuzhe Lu, Zhenlin Wang, Runtian Zhai, Soheil Kolouri, Joseph Campbell, and Katia Sycara · 2023
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