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Robust Meta-learning with Sampling Noise and Label Noise via Eigen-Reptile

ICML 2022 · Label-efficient and robust learning › Noisy labels · approach: Noise-aware loss and pairwise methods · 1 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Replace Reptile's last-step update with an update along the main direction of historical task parametersReptile · Mini-Imagenet 5-way 1-shotaccuracy: 49.97 \pm 0.32\% -> 51.80 \pm 0.90\%Helped
Replace Reptile's last-step update with an update along the main direction of historical task parametersReptile · Mini-Imagenet 5-way 5-shotaccuracy: 65.99 \pm 0.58\% -> 68.10\pm 0.50 \%Helped
Use Eigen-Reptile instead of ReptileReptile · CIFAR-FS 5-way 1-shotaccuracy: 58.30 \pm 1.20 \% -> 61.90\pm1.40\%Helped
Use Eigen-Reptile instead of ReptileReptile · CIFAR-FS 5-way 5-shotaccuracy: 75.45\pm 0.55\% -> 78.30 \pm 0.50\%Helped
Use Eigen-Reptile instead of ReptileReptile · Mini-Imagenet 5-way 1-shot with symmetric label noiseaccuracy: 47.64\% -> 47.87\% (p=0.0); 23.33\% -> 27.23\% (p=0.5)Helped
Use Eigen-Reptile instead of ReptileReptile · Mini-Imagenet 5-way 1-shot with asymmetric label noiseaccuracy: 42.03\% -> 42.29\% (p=0.5)Helped
Add ISPL sample selection to Eigen-Reptile (ablation)Eigen-Reptile · Mini-Imagenet 5-way 1-shot, symmetric label noiseaccuracy: 27.23\% -> 28.68\% (p=0.5)Helped
Add ISPL sample selection to Eigen-Reptile (ablation)Eigen-Reptile · Mini-Imagenet 5-way 1-shot, asymmetric label noiseaccuracy: 42.29\% -> 43.71\% (p=0.5)Helped
Add ISPL sample selection to Eigen-Reptile (ablation)Eigen-Reptile · Mini-Imagenet 5-way 1-shot without label noiseaccuracy: 47.87\% -> 47.26\%Hurt
Add ISPL sample selection to Reptile (ablation)Reptile · Mini-Imagenet 5-way 1-shot with label noiseaccuracy: 47.64\% -> 47.23\% (p=0.0); 23.33\% -> 21.83\% (symmetric p=0.5); 42.03\% -> 41.09\% (asymmetric p=0.5)Mixed
Use the 64-filter version instead of the 32-filter version (ablation)Eigen-Reptile · Mini-Imagenet 5-way 1-shotaccuracy: 51.80 \pm 0.90\% -> 53.25 \pm 0.45\%Helped
Use the 64-filter version instead of the 32-filter version (ablation)Eigen-Reptile · Mini-Imagenet 5-way 5-shotaccuracy: 68.10\pm 0.50 \% -> 69.85\pm 0.85 \%Helped

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