A distributed learning problem over multiple access channel (MAC) using a large wireless
network is considered. The objective function is a sum of the nodes' local loss functions. The …

We consider a distributed learning problem over multiple access channel (MAC) using a
large wireless network. The computation is made by the network edge and is based on …

We consider a distributed learning problem in a wireless network, consisting of distributed
edge devices and a parameter server (PS). The objective function is a sum of the edge …

We focus on a distributed learning problem in a communication network, consisting of
distributed nodes and a central parameter server (PS). The PS is responsible for performing …

We consider a distributed learning problem in a communication network, consisting of N
distributed nodes and a central parameter server (PS). The computation is made by the PS …

This paper considers a general class of iterative algorithms performing a distributed training
task over a network where the nodes have background traffic and communicate through a …

We study federated machine learning at the wireless network edge, where limited power
wireless devices, each with its own dataset, build a joint model with the help of a remote …

We study distributed machine learning at the wireless edge, where limited power devices
(workers) with local datasets implement distributed stochastic gradient descent (DSGD) over …

We study wireless collaborative machine learning (ML), where mobile edge devices, each
with its own dataset, carry out distributed stochastic gradient descent (DSGD) over-the-air …

This paper addresses the problem of distributed training of a machine learning model over
the nodes of a wireless communication network. Existing distributed training methods are …