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Federated-Learning

We implement the paper Communication-Efficient Learning of Deep Networks from Decentralized Data. Its blog is here.

We wish to explore several possible approaches:

  1. server pulling gradient update from clients;
  2. clients eagerly train and push updates to server;
  3. extend to multi-server; servers gossip to sync;
  4. client-only p2p gradient updates