Fairness-Aware Machine Learning: Practical Challenges and Lessons Learned-Reference-Cited by-同舟云学术

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Fairness-Aware Machine Learning: Practical Challenges and Lessons Learned

Published:2019-05-13 Issue: Volume: Page:
ISSN:
Container-title:Companion Proceedings of The 2019 World Wide Web Conference
language:
Short-container-title:

Author:

Bird Sarah¹,Hutchinson Ben²,Kenthapadi Krishnaram³,Kıcıman Emre⁴,Mitchell Margaret²

Affiliation:

1. Facebook

2. Google

3. LinkedIn Corp.

4. Microsoft

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3308560.3320086

Reference20 articles.

1. Algorithmic Decision Making and the Cost of Fairness

Cited by 13 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. AFCMiner: Finding Absolute Fair Cliques From Attributed Social Networks for Responsible Computational Social Systems;IEEE Transactions on Computational Social Systems;2023-12

2. Fairness-aware machine learning engineering: how far are we?;Empirical Software Engineering;2023-11-24

3. Learning for Counterfactual Fairness from Observational Data;Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining;2023-08-04

4. Applications of Speech Analysis in Psychiatry;Harvard Review of Psychiatry;2023-01

5. Risks and benefits of dermatological machine learning health care applications—an overview and ethical analysis;Journal of the European Academy of Dermatology and Venereology;2022-05-17

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