Efficient Machine Unlearning Using General Adversarial Network-Reference-Cited by-同舟云学术

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Efficient Machine Unlearning Using General Adversarial Network

Published:2020-07-24 Issue: Volume: Page:487-494
ISSN:2367-3370
Container-title:Artificial Intelligence Techniques for Advanced Computing Applications
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Author:

Deepanjali S.,Dhivya S.,Monica Catherine S.

Publisher

Springer Singapore

Link

http://link.springer.com/content/pdf/10.1007/978-981-15-5329-5_45

Reference10 articles.

1. BBC News-Technology. https://www.bbc.com/news/technology-49808208

2. Schlegl T, Seeböck P, Waldstein SM, Langs G, Schmidt-Erfurthb U (2019) f-AnoGAN: fast unsupervised anomaly detection with generative adversarial networks. Med Image Anal 54: 30–44, 99–110

3. Eiter T, Kern-Isberne G (2019) A brief survey on forgetting from a knowledge representation and reasoning perspective. Künstl Intell: 9–33. https://doi.org/10.1007/s13218-018-0564-6

4. Cao Y, Yang J (2015) Towards making systems forget with machine unlearning. In: 2015 IEEE symposium on security and privacy, San Jose, CA, pp 463–480. https://doi.org/10.1109/sp.2015.35

5. Jilek C, Runge Y, Niedeŕee C, Maus H, Tempel T, Dengel A, Frings C (2019) Managed Forgetting to support information management and knowledge work. https://doi.org/10.1007/s13218-018-00568-9

Cited by 2 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. Algorithms that forget: Machine unlearning and the right to erasure;Computer Law & Security Review;2023-11

2. Machine Unlearning Method Based On Projection Residual;2022 IEEE 9th International Conference on Data Science and Advanced Analytics (DSAA);2022-10-13

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