595 citations · 3.6k across the 131 of their papers we have counts for
3 papers · 2 filters
Over-the-Air Federated Learning from Heterogeneous Data
Tomer Sery, Nir Shlezinger, Kobi Cohen +1
Federated learning (FL) is a framework for distributed learning of centralized models. In FL, a set of edge devices train a model using their local data, while repeatedly exchangin…
UVeQFed: Universal Vector Quantization for Federated Learning
Nir Shlezinger, Mingzhe Chen, Yonina C. Eldar +2
Traditional deep learning models are trained at a centralized server using labeled data samples collected from end devices or users. Such data samples often include private informa…
Learned Factor Graphs for Inference from Stationary Time Sequences
Nir Shlezinger, Nariman Farsad, Yonina C. Eldar +1
The design of methods for inference from time sequences has traditionally relied on statistical models that describe the relation between a latent desired sequence and the observed…