Data Heterogeneity

Federated Learning's Architecture Explains Its Three Hardest Problems

Federated learning's core architecture, which keeps data local on clients and aggregates model updates centrally, directly causes its three main technical challenges: data and system heterogeneity, communication overhead, and security vulnerabilities. Understanding how these problems map to the client-server design is key to addressing them.