406 citations · 635 across the 64 of their papers we have counts for
9 papers · 1 filter
A Comparison of Neural Networks for Wireless Channel Prediction
Oscar Stenhammar, Gabor Fodor, Carlo Fischione
The performance of modern wireless communications systems depends critically on the quality of the available channel state information (CSI) at the transmitter and receiver. Severa…
Federated Learning Using Three-Operator ADMM
Shashi Kant, José Mairton B. da Silva, Gabor Fodor +3
Federated learning (FL) has emerged as an instance of distributed machine learning paradigm that avoids the transmission of data generated on the users' side. Although data are not…
A-LAQ: Adaptive Lazily Aggregated Quantized Gradient
Afsaneh Mahmoudi, José Mairton Barros Da Silva Júnior, Hossein S. Ghadikolaei +1
Federated Learning (FL) plays a prominent role in solving machine learning problems with data distributed across clients. In FL, to reduce the communication overhead of data betwee…
Blind Asynchronous Over-the-Air Federated Edge Learning
Saeed Razavikia, Jaume Anguera Peris, Jose Mairton B. da Silva +1
Federated Edge Learning (FEEL) is a distributed machine learning technique where each device contributes to training a global inference model by independently performing local comp…
FedCau: A Proactive Stop Policy for Communication and Computation Efficient Federated Learning
Afsaneh Mahmoudi, Hossein S. Ghadikolaei, José Mairton Barros Da Silva Júnior +1
This paper investigates efficient distributed training of a Federated Learning~(FL) model over a wireless network of wireless devices. The communication iterations of the distribut…
Dynamic Clustering in Federated Learning
Yeongwoo Kim, Ezeddin Al Hakim, Johan Haraldson +3
In the resource management of wireless networks, Federated Learning has been used to predict handovers. However, non-independent and identically distributed data degrade the accura…