Fairness by Learning Orthogonal Disentangled Representations-Reference-Cited by-同舟云学术

Fairness by Learning Orthogonal Disentangled Representations

Published:2020 Issue: Volume: Page:746-761
ISSN:0302-9743
Container-title:Computer Vision – ECCV 2020
language:
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Author:

Sarhan Mhd Hasan^ORCID,Navab Nassir,Eslami Abouzar^ORCID,Albarqouni Shadi^ORCID

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-030-58526-6_44

Reference27 articles.

1. Barocas, S., Hardt, M., Narayanan, A.: Fairness and Machine Learning. fairmlbook.org (2019). http://www.fairmlbook.org

2. Chen, R.T., Li, X., Grosse, R.B., Duvenaud, D.K.: Isolating sources of disentanglement in variational autoencoders. In: Advances in Neural Information Processing Systems, pp. 2610–2620 (2018)

3. Creager, E., et al.: Flexibly fair representation learning by disentanglement. arXiv preprint arXiv:1906.02589 (2019)

4. Dua, D., Graff, C.: UCI machine learning repository (2017)

5. Edwards, H., Storkey, A.: Censoring representations with an adversary. arXiv preprint arXiv:1511.05897 (2015)

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