… ML methods in Section III, in this section, we present communication-efficient and distributed
learning frameworks with selected use cases. The mapping between specific principles and …

… This mandates to co-design distributed ML and … to present communication-efficient and
distributed learning frameworks … wireless channel dynamics and network topology variations. To …

… In this section, we provide an overview of communication-efficient distributed learning …
efficiency for distributed learning over wireless networks. 2) Impact of Wireless Interference in …

… architectures and their applications to wireless networks. The key … wireless channels. In
a nutshell, the above-mentioned wireless DML frameworks can enable a distributed learning …

… study of how distributed learning can be efficiently and effectively deployed over wireless edge
networks… into communication-efficient FL and present the concept of federated distillation (…

… Potential distributed learning applications in wireless networks and primary future research
… DANE: A communication efficient distributed approximate Newton (DANE) algorithm is …

… problem in distributed deep learning is becoming a hot research topic recently. In this
paper, we provide a comprehensive survey of the communication-efficient distributed training …

… comprehensive study of FL over wireless networks. … wireless networks will directly impact
the learning performance. The final challenge is that efficient distributed learning over wireless …

… devise communicationefficient distributed learning algorithms … and simultaneously achieve
satisfactory learning/optimization … asynchronous federated learning over wireless networks,” …

… a comprehensive study of how distributed learning can be efficiently and effectively
deployed in wireless networks. In particular, we introduce four distributed learning frameworks, …