Unlearnable Examples Give a False Sense of Security: Piercing through Unexploitable Data with Learnable Examples

1 code implementation • 16 May 2023 • Wan Jiang, Yunfeng Diao, He Wang, Jianxin Sun, Meng Wang, Richang Hong

Unfortunately, we find UEs provide a false sense of security, because they cannot stop unauthorized users from utilizing other unprotected data to remove the protection, by turning unlearnable data into learnable again.

Deep Hierarchy Quantization Compression algorithm based on Dynamic Sampling

no code implementations • 30 Dec 2022 • Wan Jiang, Gang Liu, Xiaofeng Chen, Yipeng Zhou

Unlike traditional distributed machine learning, federated learning stores data locally for training and then aggregates the models on the server, which solves the data security problem that may arise in traditional distributed machine learning.

Federated Learning Quantization