Domain-incremental learning
Domain-incremental learning involves training machine learning models to adapt to new domains while retaining knowledge from previous ones.
catastrophic forgetting
Class-incremental learning
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.
Continual learning
Continual learning is an area of machine learning focused on enabling models to learn continuously from data streams without forgetting previously acquired knowledge. It addresses challenges such as catastrophic forgetting and aims to create adaptive systems capable of lifelong learning.