Fedstellar: A Platform for Decentralized Federated Learning. (arXiv:2306.09750v2 [cs.LG] UPDATED)

In 2016, Google proposed Federated Learning (FL) as a novel paradigm to train
Machine Learning (ML) models across the participants of a federation while
preserving data privacy. Since its birth, Centralized FL (CFL) has been the
most used approach, where a central entity aggregates participants' models to
create a global one. However, CFL presents limitations such as communication
bottlenecks, single point of failure, and reliance on a central server.
Decentralized Federated Learning (DFL) addresses these issues by enabling
decentralized model …

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