Domain-incremental learning
Domain-incremental learning involves training machine learning models to adapt to new domains while retaining knowledge from previous ones.
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Domain-incremental learning involves training machine learning models to adapt to new domains while retaining knowledge from previous ones.
Class-incremental learning is a subfield of machine learning that focuses on the ability of models to learn new classes of data incrementally without forgetting previously learned information.