OpenFed: A Comprehensive and Versatile Open-Source Federated Learning Framework. (arXiv:2109.07852v3 [cs.CR] UPDATED)

Recent developments in Artificial Intelligence techniques have enabled their
successful application across a spectrum of commercial and industrial settings.
However, these techniques require large volumes of data to be aggregated in a
centralized manner, forestalling their applicability to scenarios wherein the
data is sensitive or the cost of data transmission is prohibitive. Federated
Learning alleviates these problems by decentralizing model training, thereby
removing the need for data transfer and aggregation. To advance the adoption of
Federated Learning, more research and …

address adoption application artificial artificial intelligence commercial cost data data transfer development federated learning framework industrial intelligence large model training problems research settings spectrum techniques training transmission