… Further we analyze and summarize several ways to handle the heterogeneous and huge
data. Comprehensive background on data and resource management are then presented, …

… studies over MEC scenario mainly protect the privacy in two ways: … autonomous car should
be capable of sensing its environment and navigating without human input. Autonomous cars …

… In Section II, we present an overview and taxonomy of FL with a comprehensive list of
existing studies. In Section III, we review distributed optimization and ML approaches. Section IV …

… Section II introduces the background of this study. Section III … -end approach and validate the
on-device Federated Learning … deep learning for steering autonomous vehicles considering …

… Additionally, autonomous cars have more computational power with sufficient energy. … Since
there are different ways to implement federated learning (eg, centralized edge/cloud server-…

… Simultaneously, we review key technologies and the latest results in … approach that could
accelerate the learning process of data transmission protocols (eg TCP) that convert vehicles …

… appropriate FL approaches for autonomous vehicles and UAVs-… for reliable federated
learning: A joint optimization approach to … Beaufays, “Federated learning for emoji prediction in a …

… emerging area of federated neural architecture search. We categorize federated learning
systems into offline and online approaches, where online federated neural architecture search …

… , wearable devices and autonomous vehicles are examples of … This work aims to provide a
survey on FL for IDS in terms of … -Fed, an asynchronous online federated learning approach is …

… Federated learning emerges as an efficient approach to exploit … survey of existing works
for federated learning. First, we propose a functional architecture of federated learning systems …