2 citations · 2 across the 6 of their papers we have counts for
4 papers · 1 filter
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)…
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…
Federated Learning: A Signal Processing Perspective
Tomer Gafni, Nir Shlezinger, Kobi Cohen +2
The dramatic success of deep learning is largely due to the availability of data. Data samples are often acquired on edge devices, such as smart phones, vehicles and sensors, and i…
Distributed Learning over Markovian Fading Channels for Stable Spectrum Access
Tomer Gafni, Kobi Cohen
We consider the problem of multi-user spectrum access in wireless networks. The bandwidth is divided into K orthogonal channels, and M users aim to access the spectrum. Each user c…