TorchFL: A Performant Library for Bootstrapping Federated Learning Experiments. (arXiv:2211.00735v1 [cs.LG])

With the increased legislation around data privacy, federated learning (FL)
has emerged as a promising technique that allows the clients (end-user) to
collaboratively train deep learning (DL) models without transferring and
storing the data in a centralized, third-party server. Despite the theoretical
success, FL is yet to be adopted in real-world systems due to the hardware,
computing, and various infrastructure constraints presented by the edge and
mobile devices of the clients. As a result, simulated datasets, models, and
experiments are …

arxiv bootstrapping federated learning library