Decentral and Incentivized Federated Learning Frameworks: A Systematic Literature Review. (arXiv:2205.07855v2 [cs.LG] UPDATED)

The advent of Federated Learning (FL) has ignited a new paradigm for parallel
and confidential decentralized Machine Learning (ML) with the potential of
utilizing the computational power of a vast number of IoT, mobile and edge
devices without data leaving the respective device, ensuring privacy by design.
Yet, in order to scale this new paradigm beyond small groups of already
entrusted entities towards mass adoption, the Federated Learning Framework
(FLF) has to become (i) truly decentralized and (ii) participants have …

arxiv federated learning frameworks learning literature review