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Improved modelling of federated datasets using mixtures-of-Dirichlet-multinomials
In practice, training using federated learning can be orders of magnitude slower than standard centralized training. This severely limits the amount of experimentation and tuning that can be done, making it challenging to obtain good performance on a given task. Server-side proxy data can be used to
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