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Differential privacy for deep and federated learning: A survey
Users' privacy is vulnerable at all stages of the deep learning process. Sensitive information
of users may be disclosed during data collection, during training, or even after releasing the …
of users may be disclosed during data collection, during training, or even after releasing the …
Differentially private natural language models: Recent advances and future directions
L Hu, I Habernal, L Shen, D Wang - ar** machine learning methods that are privacy preserving is today a central topic of
research, with huge practical impacts. Among the numerous ways to address privacy …
research, with huge practical impacts. Among the numerous ways to address privacy …
Local Differential Privacy Is Equivalent to Contraction of an -Divergence
We investigate the local differential privacy (LDP) guarantees of a randomized privacy
mechanism via its contraction properties. We first show that LDP constraints can be …
mechanism via its contraction properties. We first show that LDP constraints can be …