Socially Responsible Machine Learning: A Causal Perspective-Reference-Cited by-同舟云学术

Socially Responsible Machine Learning: A Causal Perspective

Published:2023-08-04 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
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Author:

Moraffah Raha¹^ORCID,Karimi Amir-Hossein²^ORCID,Raglin Adrienne³^ORCID,Liu Huan¹^ORCID

Affiliation:

1. Arizona State University, Tempe, AZ, USA

2. Max Planck Institute for Intelligent Systems, Tübingen, Germany

3. Army Research Lab, Maryland, MD, USA

Funder

Army Research Office

Army Research Laboratory

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3580305.3599571

Reference23 articles.

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2. Haoyue Bai et al. 2021 . Decaug: Out-of-distribution generalization via decomposed feature representation and semantic augmentation. In AAAI. Haoyue Bai et al. 2021. Decaug: Out-of-distribution generalization via decomposed feature representation and semantic augmentation. In AAAI.

3. Solon Barocas Moritz Hardt and Arvind Narayanan. 2019. Fairness and Machine Learning: Limitations and Opportunities. http://www.fairmlbook.org. Solon Barocas Moritz Hardt and Arvind Narayanan. 2019. Fairness and Machine Learning: Limitations and Opportunities. http://www.fairmlbook.org.

4. Yang Chen Yu Wang Yingwei Pan Ting Yao Xinmei Tian and Tao Mei. 2021. A style and semantic memory mechanism for domain generalization. In ICCV. Yang Chen Yu Wang Yingwei Pan Ting Yao Xinmei Tian and Tao Mei. 2021. A style and semantic memory mechanism for domain generalization. In ICCV.

5. Cynthia Dwork , Nicole Immorlica , Adam Tauman Kalai , and Max Leiserson . 2018 . Decoupled classifiers for group-fair and efficient machine learning . In Conference on fairness, accountability and transparency. PMLR, 119--133 . Cynthia Dwork, Nicole Immorlica, Adam Tauman Kalai, and Max Leiserson. 2018. Decoupled classifiers for group-fair and efficient machine learning. In Conference on fairness, accountability and transparency. PMLR, 119--133.