Image Classification on TinyImageNet Forgotten (train)
64.2AccuracySCRUB
Evaluation Results
| Method | Links | ||
|---|---|---|---|
| SCRUBUnlearning Scenario=Random Data Forgetting, Forgetting Ratio=30%, Backbone=ResNet2026.04 | 64.2 | 17.2 | |
| SCRUBUnlearning Scenario=Random Data Forgetting, Forgetting Ratio=50%, Backbone=ResNet2026.04 | 63.2 | 20.3 | |
| FTUnlearning Scenario=Random Data Forgetting, Forgetting Ratio=30%, Backbone=ResNet2026.04 | 60.9 | 13.9 | |
| FTUnlearning Scenario=Random Data Forgetting, Forgetting Ratio=50%, Backbone=ResNet2026.04 | 59.5 | 16.5 | |
| IEU w/GAUnlearning Scenario=Random Data Forgetting, Forgetting Ratio=30%, Backbone=ResNet2026.04 | 54.7 | 7.7 | |
| RLUnlearning Scenario=Random Data Forgetting, Forgetting Ratio=50%, Backbone=ResNet2026.04 | 52.5 | 9.6 | |
| IEU w/GAUnlearning Scenario=Random Data Forgetting, Forgetting Ratio=50%, Backbone=ResNet2026.04 | 52.5 | 9.5 | |
| IEU w/GA+NoisyUnlearning Scenario=Random Data Forgetting, Forgetting Ratio=30%, Backbone=ResNet2026.04 | 51.8 | 4.8 | |
| RLUnlearning Scenario=Random Data Forgetting, Forgetting Ratio=30%, Backbone=ResNet2026.04 | 51.2 | 4.2 | |
| IEU w/NoisyUnlearning Scenario=Random Data Forgetting, Forgetting Ratio=30%, Backbone=ResNet2026.04 | 50.8 | 3.8 | |
| SALUNUnlearning Scenario=Random Data Forgetting, Forgetting Ratio=30%, Backbone=ResNet2026.04 | 50.7 | 3.6 | |
| IEU w/GA+NoisyUnlearning Scenario=Random Data Forgetting, Forgetting Ratio=50%, Backbone=ResNet2026.04 | 48.6 | 5.6 | |
| IEU w/NoisyUnlearning Scenario=Random Data Forgetting, Forgetting Ratio=50%, Backbone=ResNet2026.04 | 48.3 | 5.4 | |
| RetrainingUnlearning Scenario=Random Data Forgetting, Forgetting Ratio=30%, Backbone=ResNet2026.04 | 47 | 0 | |
| SALUNUnlearning Scenario=Random Data Forgetting, Forgetting Ratio=50%, Backbone=ResNet2026.04 | 45.4 | 2.5 | |
| RetrainingUnlearning Scenario=Random Data Forgetting, Forgetting Ratio=50%, Backbone=ResNet2026.04 | 42.9 | 0 |