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Online federated learning (OFL) and online transfer learning (OTL) are twocollaborative paradigms for overcoming modern machine learning challenges suchas data silos, streaming data, and data security. This survey explored OFL andOTL throughout their major evolutionary routes to enhance understanding ofonline federated and transfer learning. Besides, practical aspects of populardatasets and cutting-edge applications for online federated and transferlearning are highlighted in this work. Furthermore, this survey providesinsight into potential future research areas and aims to serve as a resourcefor professionals developing online federated and transfer learning frameworks.

Addressing modern and practical challenges in machine learning: A survey of online federated and transfer learning