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cs.LG2023
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…
cs.LG2023
Model-aided Federated Reinforcement Learning for Multi-UAV Trajectory Planning in IoT Networks
Jichao Chen, Omid Esrafilian, Harald Bayerlein +2
Deploying teams of unmanned aerial vehicles (UAVs) to harvest data from distributed Internet of Things (IoT) devices requires efficient trajectory planning and coordination algorit…