Exploring aggregation strategies for federated learning in national statistics 1

B. Santos Julian Templeton Rafik Chemli Statistics Canada E. Cerasti Francesco Pugliese Mauro Bruno M. De Cubellis

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TL;DR

A weighted Federated Averaging aggregation scheme which aims to highlight the potential benefits of positively weighing clients who contain more homogeneous data and the preliminary results exhibit that when clients with more homogeneous data are weighed higher, the global model can achieve better performance, but that a sufficiently complex FL task is needed for these effects to be more prevalent.

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