… federated learning for computation offloading in a separated section as the federated learning
… As the optimization tool, federated learning is considered the optimizer for designing the …

… tion approach for on-device federated learning via over-the-air computation. To improve
the performance and the convergence rate for federated learning, we propose a joint device …

… In this article, we propose an asynchronously updating federated learning model for the
edge nodes to build local artificial intelligence models for smart remote sensing with a forest fire …

… Based on machine learning and deep learning, we propose a semi-supervised learning …
Finally, we build a collaborative federated learning architecture for anomaly traffic detection …

… predict the air quality index (AQI). To this end, this article proposes a new federated learning
(FL)-based aerial-ground air quality sensing framework for fine-grained 3-D air quality mon…

A space–air–ground–sea integrated network (SAGSIN) is a promising heterogeneous network
framework for the next generation mobile communications. Moreover, federated learning (…

… To address these issues, we propose to leverage the popular federated learning to … -air-space
topology naturally forms the star structure, we integrate the standard federated learning (eg…

… novel configurable federated learning framework in the SAGIN environment, namely
Olive Branch … We consider a federated learning based model training scenario in space-air-ground …

… As such, distributed machine learning is well motivated to overcome these … learning,
federated learning (FL) has been proposed as a well noted approach for collaborative learning [3]. …

… This protocol aims to provide a threshold signing scheme in industrial blockchain-based
federated learning. The goal of federated learning is to train a global model W . In the process of …