Federated, Online, Active and Continual Learning
Train across devices without sharing raw data (federated), update as data streams in (online), ask humans to label the most useful examples (active), and keep learning without forgetting (continual).
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Each tackles a practical limit: privacy, changing data, or labelling cost.
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