64 citations · 113 across the 12 of their papers we have counts for
3 papers · 1 filter
DP-REC: Private & Communication-Efficient Federated Learning
Aleksei Triastcyn, Matthias Reisser, Christos Louizos
Privacy and communication efficiency are important challenges in federated training of neural networks, and combining them is still an open problem. In this work, we develop a meth…
An Expectation-Maximization Perspective on Federated Learning
Christos Louizos, Matthias Reisser, Joseph Soriaga +1
Federated learning describes the distributed training of models across multiple clients while keeping the data private on-device. In this work, we view the server-orchestrated fede…
Federated Mixture of Experts
Matthias Reisser, Christos Louizos, Efstratios Gavves +1
Federated learning (FL) has emerged as the predominant approach for collaborative training of neural network models across multiple users, without the need to gather the data at a…