1 citations · 1 across the 5 of their papers we have counts for
6 papers
Communication-Efficient Federated Learning via Regularized Sparse Random Networks
Mohamad Mestoukirdi, Omid Esrafilian, David Gesbert +2
This work presents a new method for enhancing communication efficiency in stochastic Federated Learning that trains over-parameterized random networks. In this setting, a binary ma…
User-Centric Federated Learning: Trading off Wireless Resources for Personalization
Mohamad Mestoukirdi, Matteo Zecchin, David Gesbert +1
Statistical heterogeneity across clients in a Federated Learning (FL) system increases the algorithm convergence time and reduces the generalization performance, resulting in a lar…
UAV-Aided Multi-Community Federated Learning
Mohamad Mestoukirdi, Omid Esrafilian, David Gesbert +1
In this work, we investigate the problem of an online trajectory design for an Unmanned Aerial Vehicle (UAV) in a Federated Learning (FL) setting where several different communitie…
User-Centric Federated Learning
Mohamad Mestoukirdi, Matteo Zecchin, David Gesbert +2
Data heterogeneity across participating devices poses one of the main challenges in federated learning as it has been shown to greatly hamper its convergence time and generalizatio…
Robust Regularized ZF in Cooperative Broadcast Channel under Distributed CSIT
Qianrui Li, Paul de Kerret, David Gesbert +1
In this work, we consider the sum rate performance of joint processing coordinated multi-point transmission network (JP-CoMP, a.k.a Network MIMO) in a so-called distributed channel…
Cooperative Channel Estimation for Coordinated Transmission with Limited Backhaul
Qianrui Li, David Gesbert, Nicolas Gresset
Obtaining accurate global channel state information (CSI) at multiple transmitter devices is critical to the performance of many coordinated transmission schemes. Practical CSI loc…