Synthesizing prototypical exemplars and perturbation-based variants enables rehearsal-based continual learning with substantially fewer samples per class than standard coreset methods.
Gradient episodic memory for continual learning.Advances in neu- ral information processing systems, 30, 2017
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DLC inserts lightweight classifier-proximal plugins into distillation-based continual learning to achieve 8% accuracy gains on large benchmarks with only 4% extra backbone parameters.
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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.
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Pushing the Limits of Distillation-Based Continual Learning via Classifier-Proximal Lightweight Plugins
DLC inserts lightweight classifier-proximal plugins into distillation-based continual learning to achieve 8% accuracy gains on large benchmarks with only 4% extra backbone parameters.