… to tackle the privacy issues in deep and federated learning (FL). Particularly, we focus on
differential privacy (DP) which became a de facto standard for protecting users’ privacy in …

… framework based on the concept of differential privacy (DP), in … privacy protection levels,
ie, better convergence performance leads to a lower protection level; 2) given a fixed privacy …

… Then, we develop a distributed learning scheme to achieve personalized federated learning
with differential privacy guarantee in Section IV. Next, we analyze the convergence rate of …

… federated learning system with a formal privacy guarantee using local differential privacy (LDP)…
Existing LDP protocols are developed primarily to ensure data privacy in the collection of …

… federated learning with formal privacy guarantees. We propose to employ Bayesian differential
privacy, a relaxation of differential privacy … privacy loss bounds. We adapt the Bayesian …

… federated learning (FL) over a wireless channel, modeled by a Gaussian multiple access
channel (MAC), subject to local differential … K users, the privacy leakage per user scales as O( 1 …

… 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 …

… explore federated learning (FL) as a collaborative learning … using federated learning with
additional privacy preservation … the privacy using Rényi Differential Privacy Accountant 4 . We …

… framework cannot completely guarantee the privacy security of users. Motivated … federated
learning scheme combined with the adaptive gradient descent strategy and differential privacy …

… 1In this paper, we use an abstraction for the federated learning model, … learning with local
differential privacy guarantees, which has fewer results, especially in the shuffled privacy frame…