Advancements in Federated Learning: Models, Methods, and Privacy

Understand

Federated learning (FL) is a promising technique for addressing the rising privacy and security issues.

• Its main ingredient is to cooperatively learn the model among the distributed clients without uploading any sensitive data.
• In this paper, we conducted a thorough review of the related works, following the development context and deeply mining the key technologies behind FL from both theoretical and practical perspectives.
• Specifically, we first classify the existing works in FL architecture based on the network topology of FL systems with detailed analysis and summarization.