What are some effective strategies for federated learning?

What are some effective strategies for federated learning?

Effective strategies for federated learning include model averaging, secure aggregation, and personalized models.

Can you explain model averaging in more detail?

Model averaging involves aggregating the updates from multiple local models to create a global model, ensuring privacy.

What are the challenges associated with federated learning?

Challenges include data heterogeneity, communication costs, and ensuring model convergence across different devices.

How can we ensure data privacy in federated learning?

Data privacy can be ensured through techniques like differential privacy and secure multi-party computation.