NeuronFair-Reference-Cited by-同舟云学术

NeuronFair

Published:2022-05-21 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 44th International Conference on Software Engineering
language:
Short-container-title:

Author:

Zheng Haibin¹,Chen Zhiqing²,Du Tianyu²,Zhang Xuhong²,Cheng Yao³,Ji Shouling²,Wang Jingyi²,Yu Yue⁴,Chen Jinyin¹

Affiliation:

1. Zhejiang University of Technology

2. Zhejiang University

3. Huawei International

4. National University of Defense Technology

Funder

Zhejiang Provincial Natural Science Foundation for Distinguished Young Scholars

Ten Thousand Talents Program' in Zhejiang Province

National Natural Science Foundation of China

Key R&D Projects in Zhejiang Province

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3510003.3510123

Reference61 articles.

1. Julius Adebayo and Lalana Kagal . 2016. Iterative Orthogonal Feature Projection for Diagnosing Bias in Black-Box Models. CoRR abs/1611.04967 ( 2016 ), 1--5. arXiv:1611.04967 http://arxiv.org/abs/1611.04967 Julius Adebayo and Lalana Kagal. 2016. Iterative Orthogonal Feature Projection for Diagnosing Bias in Black-Box Models. CoRR abs/1611.04967 (2016), 1--5. arXiv:1611.04967 http://arxiv.org/abs/1611.04967

2. Aniya Aggarwal , Pranay Lohia , Seema Nagar , Kuntal Dey , and Diptikalyan Saha . 2018. Automated Test Generation to Detect Individual Discrimination in AI Models. CoRR abs/1809.03260 ( 2018 ), 1--8. arXiv:1809.03260 http://arxiv.org/abs/1809.03260 Aniya Aggarwal, Pranay Lohia, Seema Nagar, Kuntal Dey, and Diptikalyan Saha. 2018. Automated Test Generation to Detect Individual Discrimination in AI Models. CoRR abs/1809.03260 (2018), 1--8. arXiv:1809.03260 http://arxiv.org/abs/1809.03260

3. Black box fairness testing of machine learning models

4. Uncovering and Mitigating Algorithmic Bias through Learned Latent Structure

5. Application of deep learning for retinal image analysis: A review

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