Federated Learning Survey: Aggregation Techniques, Experiments, and Future Directions

This ArXiv paper provides a comprehensive overview of federated learning, a crucial area for privacy-preserving machine learning. The survey's focus on aggregation techniques and experimental insights is especially valuable for researchers and practitioners.

• •Provides a multi-level taxonomy of aggregation techniques.
• •Offers experimental insights into various federated learning approaches.
• •Highlights future frontiers and research directions in the field.