… To this end, we propose the adoption of a Federated Learning (FL) based approach to
enable privacy-preserving collaborative Machine Learning across a federation of independent …

… propose a vehicle CP system based on federated learning (… 2) in the user level, the federated
learning method is adopted to … application level, a federated learning algorithm is deployed …

… In this paper, we propose a new architecture based on federated learning to relieve … an
asynchronous federated learning scheme by adopting Deep Reinforcement Learning (DRL) for …

… Federated Learning (FL) has emerged as a distributed collaborative AI approach that can
enable many intelligent IoT applications, by allowing for AI training at distributed IoT devices …

… applied to an ITS, reinforcement learning (RL) and federated learning (FL) are two standout
options. RL is an intelligence method capable of learning complex policy decisions in a …

… In this study, a two-layer federated learning model is proposed … more efficient and more
accurate learning while ensuring data … as a part of the federated learning process to better utilize …

… a hierarchical federated learning algorithm are proposed for knowledge sharing, by which
vehicles learn environmental data through machine learning methods and share the learning …

… federated learning: a joint optimization approach to combining reputation and contract theory,”
IEEE Internet … Han, “Federated learning in vehicular edge computing: A selective model …

… , which enriched the scope of federated learning. The characteristic … vehicle nodes makes
it very suitable for federated learning, and many researchers have applied federated learning …

… Federated learning (FL) is a distributed machine learning approach that can achieve the
purpose of collaborative learning … In this paper we use FL to denote the federated learning with …