… to train a learning model locally. … learning frameworks is federatedlearning (FL) developed in [5]. FL is a distributed machine learning method that enables users to collaboratively learn …
… learning accuracy level, and thus (ii) between the FederatedLearning time and UE energy consumption… We fill this gap by formulating a FederatedLearning over wirelessnetwork as an …
… In Section III, we detail the local computing and parameter update process to run FL in wirelessnetworks. In Section IV, we analyze the convergence rate of federatedlearning under …
… resource allocation for federatedlearning (FL) over wireless communication networks is investigated… Since FL involves an exchange of a learning model between users and the BS, both …
… wirelessnetwork in training a shared ML model without data exchanges, federatedlearning … a number of existing works (eg, [3–6]) have studied its use for wirelessnetwork optimization. …
… machine learning technique called FederatedLearning (FL), … We then employ FEDL in wireless networks as a resource … Even though the wireless resource allocation problem of FEDL is …
… Since all of the FL model parameters are transmitted over wirelessnetworks, we must consider the effect of wireless factors such as resource blocks, user selection, dynamic wireless …
MM Amiri, D Gündüz - IEEE Transactions on Wireless …, 2020 - ieeexplore.ieee.org
… study federated machine learning at the wirelessnetwork edge, where limited power wireless … We consider a bandwidth-limited fading multiple access channel (MAC) from the wireless …
… , and game theory to optimize the performance of federatedlearning over wirelessnetworks. In the final part, we present several applications of federatedlearning in wirelessnetworks. …