11 citations · 25 across the 32 of their papers we have counts for
3 papers · 1 filter
Adaptive Federated Learning Over the Air
Chenhao Wang, Zihan Chen, Nikolaos Pappas +3
We propose a federated version of adaptive gradient methods, particularly AdaGrad and Adam, within the framework of over-the-air model training. This approach capitalizes on the in…
Version age-based client scheduling policy for federated learning
Xinyi Hu, Nikolaos Pappas, Howard H. Yang
Federated Learning (FL) has emerged as a privacy-preserving machine learning paradigm facilitating collaborative training across multiple clients without sharing local data. Despit…
Backward Compatibility During Data Updates by Weight Interpolation
Raphael Schumann, Elman Mansimov, Yi-An Lai +3
Backward compatibility of model predictions is a desired property when updating a machine learning driven application. It allows to seamlessly improve the underlying model without…