AINeutralarXiv – CS AI · Jun 117/10
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Federated continual learning: A comprehensive survey on lifelong and privacy-preserving learning over distributed and non-stationary data
A comprehensive survey examines Federated Continual Learning (FCL), which combines federated learning's privacy-preserving distributed training with continual learning's ability to adapt to evolving data. The research addresses a critical gap in current FL systems that assume static data, proposing frameworks for real-world applications like healthcare and IoT where data streams continuously shift, causing performance degradation and catastrophic forgetting.