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Online Continual Learning on a Contaminated Data Stream With Blurry Task Boundaries

CVPR 2022 · Continual learning › Online and replay-based · approach: Plug-and-play online training enhancements · 29 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Use PuriDivER instead of the strongest reported baselineonline blurry continual learning · CIFAR-10 SYM-40%last test accuracy: 50.9 -> 59.2Helped
Use PuriDivER instead of the strongest reported baselineonline blurry continual learning · CIFAR-100 SYM-60%last test accuracy: 14.8 -> 28.8Helped
Use PuriDivER instead of the strongest reported baselineonline blurry continual learning · WebVisionlast validation accuracy: 23.1 -> 25.8Helped
Use PuriDivER instead of the strongest reported baselineonline blurry continual learning · Food-101Nlast validation accuracy: 12.0 -> 13.4Helped
Add re-labeling and consistency regularization together (ablation)PuriDivER memory training · CIFAR-10 SYM-60%last test accuracy: 46.9 -> 52.4Helped
Add consistency regularization to re-labeling (ablation)PuriDivER memory training · CIFAR-10 SYM-60%last test accuracy: 44.1 -> 52.4Helped
Add re-labeling to consistency regularization (ablation)PuriDivER memory training · CIFAR-10 SYM-60%last test accuracy: 31.3 -> 52.4Helped
Use re-labeling alone instead of neither robust-learning component (ablation)PuriDivER memory training · CIFAR-10 SYM-20%last test accuracy: 61.8 -> 57.7Hurt
Use consistency regularization alone instead of neither robust-learning component (ablation)PuriDivER memory training · CIFAR-10 SYM-20%last test accuracy: 61.8 -> 48.6Hurt
Replace adaptive α with static α=0.6 (ablation)PuriDivER memory sampling · CIFAR-10 SYM-20%last test accuracy: 29.5Hurt
Replace adaptive α with static α=1.0 (ablation)PuriDivER memory sampling · CIFAR-10 SYM-20%last test accuracy: 26.1Hurt
Use SELFIE with memory samplingRSV, GBS, or RM · online noisy-label continual learninglast accuracyNo clear effect

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