… % and federated machine learning generally performs … local differential privacy can benefit
more from a larger client population ( > 1k). As for privacy guarantee, local differential privacy …

… To avoid the privacy threat and reduce the … to integrate federated learning and local differential
privacy (LDP) to facilitate the crowdsourcing applications to achieve the machine learning …

… Practical secure aggregation for privacy-preserving machine learning. In Proceedings of
the 2017 ACM SIGSAC Conference on Computer and Communications Security. ACM, 1175–…

… for privacy-preserving federated learning on deep learning in a cross-silo setting. LDPFL
utilizes the concepts of local differential privacy (LDP), Randomized Aggregatable Privacy-…

… PS to jointly train a machine learning model over a Gaussian MAC. The interaction between
the users and the PS must satisfy local differential privacy (LDP) constraints for each user. …

… (FL) allows to train a massive amount of data privately due to its decentralized … local differential
privacy (LDP) of user data in the FL model with SGD. The trade-offs between user privacy, …

… to Machine Learning (ML), where training data is pooled at a central server, and the alternative
of only training local … Each client trains the model with their local data for 5 epochs with …

… data collection risks severe privacy leakage if the data collector is untrustworthy. To protect
text data privacy while allowing accurate model training, we investigate federated learning of …

… used datasets in prior differential privacy work, MNIST, Fashion-MNIST and CIFAR-10,
demonstrate that our solution can not only achieve superior deep learning performance but also …

… Local Differential Privacy (LDP) to add controllable noises for protecting data privacy and …
Federated learning is a kind of distributed machine learning[9, 23]. Given 𝐾 random clients …