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What is Adapting Federated Learning To Dynamic and Non-Stationary Data An Online Learning Approach about?

This paper discusses the integration of Online Learning and Federated Learning (FL) to address the challenges of dynamic and non-stationary data in distributed machine learning. It highlights the need for adaptability, privacy preservation, and communication efficiency in Online Federated Learning (OFL), while also identifying key methodologies, challenges, and practical applications. The authors propose future research directions to enhance OFL

Author

ranjanimpdocs78

Language

EN