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Anti-discrimination learning: a causal modeling-based framework · Study

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ArticleAnti-discrimination learning: a causal modeling-based framework

Lu Zhang2017

OA

Articlebronze2017

Anti-discrimination learning: a causal modeling-based framework

Lu Zhang · Xintao Wu

48 citations·0/0 files stored·International Journal of Data Science and Analytics

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Ethics and Social Impacts of AI Privacy-Preserving Technologies in Data Explainable Artificial Intelligence (XAI)

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References

2012Fairness through awareness 2014Big Data's Disparate Impact 2016Equality of Opportunity in Supervised Learning 2015Certifying and Removing Disparate Impact 2011Data preprocessing techniques for classification without discrimination 2013Learning Fair Representations 2010Three naive Bayes approaches for discrimination-free classification 2008Discrimination-aware data mining

Cited by

2018On Discrimination Discovery and Removal in Ranked Data using Causal Graph 2019On Convexity and Bounds of Fairness-aware Classification 2020Survey on Causal-based Machine Learning Fairness Notions 2021Socially Responsible AI Algorithms: Issues, Purposes, and Challenges 2023What-is and How-to for Fairness in Machine Learning: A Survey, Reflection, and Perspective 2020Fairness through Equality of Effort 2019

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Papers that cite the same references — the relational fallback while embeddings are still backfilling.

2019Causal Modeling-Based Discrimination Discovery and Removal: Criteria, Bounds, and Algorithmsarticle · 17 shared references 2017Achieving Non-Discrimination in Data Releaseother · 16 shared references 2022Integrating Behavioral, Economic, and Technical Insights to Understand and Address Algorithmic Bias: A Human-Centric Perspectivearticle · 13 shared references 2021Fair Top-k Ranking with multiple protected groupsarticle · 12 shared references 2023Learning fair representations via an adversarial frameworkarticle · 12 shared references 2016On Discrimination Discovery Using Causal Networksother · 12 shared references

Details

Year2017

Typearticle

Published2017-05-18

VenueInternational Journal of Data Science and Analytics

ISSN-L2364-415X

Languageen

Citations48

Files0 public / 0

ShelfEthics and Social Impacts of AI

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doi10.1007/s41060-017-0058-x

openalex_workW2616536620

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Improving Prediction Fairness via Model Ensemble

2019A Distributed Fair Machine Learning Framework with Private Demographic Data Protection