What are the main challenges in federated learning?

What are the main challenges in federated learning?

Federated learning faces several challenges, including data heterogeneity, communication efficiency, and privacy concerns.

Can you explain data heterogeneity in more detail?

Data heterogeneity refers to the differences in data distribution across devices, which can affect model performance.

How does communication efficiency impact federated learning?

Communication efficiency is crucial as frequent data exchanges can lead to high latency and increased costs.

What privacy concerns should we be aware of?

Privacy concerns include the risk of data leakage and the need for secure aggregation methods to protect user data.