FairBoost: Boosting supervised learning for learning on multiple sensitive features-Reference-Cited by-同舟云学术

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FairBoost: Boosting supervised learning for learning on multiple sensitive features

Published:2023-11 Issue: Volume:280 Page:110999
ISSN:0950-7051
Container-title:Knowledge-Based Systems
language:en
Short-container-title:Knowledge-Based Systems

Author:

Colakovic Ivona^ORCID,Karakatič Sašo^ORCID

Funder

Javna Agencija za Raziskovalno Dejavnost RS

Publisher

Elsevier BV

Subject

Artificial Intelligence,Information Systems and Management,Management Information Systems,Software

Reference49 articles.

1. J. Buolamwini, Opinion — When the Robot Doesn’t See Dark Skin, The New York Times, 2018, https://www.nytimes.com/2018/06/21/opinion/facial-analysis-technology-bias.html.

2. Bias in computer systems;Friedman;ACM Trans. Inf. Syst.,1996

3. Learning fair representations;Zemel,2013

4. Machine bias;Angwin,2016

5. Amazon doesn’t consider the race of its customers. Should it?;Ingold,2016

Cited by 1 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. A Novel Approach for Model Interpretability and Domain Aware Fine-Tuning in AdaBoost;Human-Centric Intelligent Systems;2024-09-08

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