Synthesizing prototypical exemplars and perturbation-based variants enables rehearsal-based continual learning with substantially fewer samples per class than standard coreset methods.
Squeeze, recover and relabel: Dataset condensation at imagenet scale from a new perspective.Advances in Neural Information Process- ing Systems, 36:73582–73603, 2023
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Memory-efficient Continual Learning with Prototypical Exemplar Condensation
Synthesizing prototypical exemplars and perturbation-based variants enables rehearsal-based continual learning with substantially fewer samples per class than standard coreset methods.