List your company

Machine Unlearning on Tiny-Imagenet Random Forget 50%, γ=0 (test)

4.32MIAl1-sparse
0.680825.245449.8174.3746Jan 26, 2026Feb 7, 2026Feb 19, 2026Mar 4, 2026Mar 16, 2026Mar 28, 2026Apr 10, 2026

Evaluation results

MethodLinks
l1-sparseBackbone=Vgg-16, Random Forget Ratio=50%, γ (Imbalance Factor)=02026.014.3295.6895.4855.4532.37———
IUBackbone=Vgg-16, Random Forget Ratio=50%, γ (Imbalance Factor)=02026.014.3495.6595.555.6532.41———
BSBackbone=Vgg-16, Random Forget Ratio=50%, γ (Imbalance Factor)=02026.014.3495.6695.4755.0332.26———
BEBackbone=Vgg-16, Random Forget Ratio=50%, γ (Imbalance Factor)=02026.014.3695.6495.4755.2932.32———
FTBackbone=Vgg-16, Random Forget Ratio=50%, γ (Imbalance Factor)=02026.014.4195.5999.9954.7131.02———
GABackbone=Vgg-16, Random Forget Ratio=50%, γ (Imbalance Factor)=02026.014.4295.5895.4955.4532.32———
FalWBackbone=Vgg-16, Random Forget Ratio=50%, γ (Imbalance Factor)=02026.0157.2441.7699.9940.530.85———
RetrainBackbone=Vgg-16, Random Forget Ratio=50%, γ (Imbalance Factor)=02026.0159.440.699.9940.630———
SFRonBackbone=Vgg-16, Random Forget Ratio=50%, γ (Imbalance Factor)=02026.0161.138.8999.9940.450.9———
SalUnBackbone=Vgg-16, Random Forget Ratio=50%, γ (Imbalance Factor)=02026.0161.5138.4997.2136.232.85———
RLBackbone=Vgg-16, Random Forget Ratio=50%, γ (Imbalance Factor)=02026.0167.8432.1696.9137.335.82———
RetrainingBackbone=ViT2026.0489.1———073.531.434.7
RLBackbone=ViT2026.0489.9———8.654.540.640.2
SALUNBackbone=ViT2026.0491.4———13.431.227.929.3
SCRUBBackbone=ViT2026.0494.8———9.257.140.840.3
IEU w/GA+NoisyBackbone=ViT2026.0495———3.479.433.235
FTBackbone=ViT2026.0495.1———4.47238.737.6
IEU w/NoisyBackbone=ViT2026.0495.1———3.479.233.234.8
IEU w/GABackbone=ViT2026.0495.3———4.582.634.134.7