most citedFederated Learning from Heterogeneous Data via Controlled Bayesian Air Aggregation

2 citations · 2 across the 2 of their papers we have counts for

collaborators

2 papers

eess.SP2024

SINR-Aware Deep Reinforcement Learning for Distributed Dynamic Channel Allocation in Cognitive Interference Networks

Yaniv Cohen, Tomer Gafni, Ronen Greenberg +1

We consider the problem of dynamic channel allocation (DCA) in cognitive communication networks with the goal of maximizing a global signal-to-interference-plus-noise ratio (SINR)…

eess.SP2023★ 2 cited

Federated Learning from Heterogeneous Data via Controlled Bayesian Air Aggregation

Tomer Gafni, Kobi Cohen, Yonina C. Eldar

Federated learning (FL) is an emerging machine learning paradigm for training models across multiple edge devices holding local data sets, without explicitly exchanging the data. R…