Optimizing Region of Convergence to Preserve Model Privacy from Membership Inference Attack
Author:
Affiliation:
1. VNU University of Engineering and Technology,HMI Lab,Hanoi,Vietnam
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10298834/10298844/10299529.pdf?arnumber=10299529
Reference21 articles.
1. Comprehensive Privacy Analysis of Deep Learning: Passive and Active White-box Inference Attacks against Centralized and Federated Learning
2. Special properties of gradient descent with large learning rates;mohtashami;Proceedings of the 40th International Conference on Machine Learning ser Proceedings of Machine Learning Research,0
3. Systematic evaluation of privacy risks of machine learning models;song;30th USENIX Security Symposium (USENIX Security 21),2021
4. Comprehensive Privacy Analysis of Deep Learning: Passive and Active White-box Inference Attacks against Centralized and Federated Learning
5. Deep residual learning for image recognition;he;CoRR vol abs/1512 03385,2015
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