USP jointly improves unlabeled learning, memory stability, and plasticity in semi-supervised continual learning via feature-space reservation, divide-and-conquer pseudo-labeling, and class-mean distillation.
Rainbow memory: Continual learning with a memory of diverse samples
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Divide-and-Conquer for Enhancing Unlabeled Learning, Stability, and Plasticity in Semi-supervised Continual Learning
USP jointly improves unlabeled learning, memory stability, and plasticity in semi-supervised continual learning via feature-space reservation, divide-and-conquer pseudo-labeling, and class-mean distillation.