Machine Unlearning on CIFAR-100 (forget set)
18.511Avg Increase in Forget AccuracySharpMinMax
Evaluation Results
| Method | Links | |
|---|---|---|
| SharpMinMaxRelearn learning rate=0.004, Attack optimizer (A)=ASAM, Model architecture=ResNet502025.06 | 18.511 | |
| SharpMinMaxRelearn learning rate=0.003, Attack optimizer (A)=ASAM, Model architecture=ResNet502025.06 | 17.5 | |
| SharpMinMaxRelearn learning rate=0.004, Attack optimizer (A)=SGD, Model architecture=ResNet502025.06 | 16.144 | |
| SharpMinMaxRelearn learning rate=0.003, Attack optimizer (A)=SGD, Model architecture=ResNet502025.06 | 15.589 | |
| SharpMinMaxRelearn learning rate=0.002, Attack optimizer (A)=ASAM, Model architecture=ResNet502025.06 | 15.067 | |
| NGRelearn learning rate=0.004, Attack optimizer (A)=ASAM, Model architecture=ResNet502025.06 | 14.7 | |
| NG + ASAMRelearn learning rate=0.004, Attack optimizer (A)=ASAM, Model architecture=ResNet502025.06 | 13.389 | |
| NGRelearn learning rate=0.003, Attack optimizer (A)=ASAM, Model architecture=ResNet502025.06 | 13.256 | |
| SharpMinMaxRelearn learning rate=0.002, Attack optimizer (A)=SGD, Model architecture=ResNet502025.06 | 13.1 | |
| NG + ASAMRelearn learning rate=0.004, Attack optimizer (A)=SGD, Model architecture=ResNet502025.06 | 13.022 | |
| NGRelearn learning rate=0.004, Attack optimizer (A)=SGD, Model architecture=ResNet502025.06 | 12.789 | |
| SharpMinMax + ASAMRelearn learning rate=0.004, Attack optimizer (A)=SGD, Model architecture=ResNet502025.06 | 12.711 | |
| SharpMinMax + ASAMRelearn learning rate=0.004, Attack optimizer (A)=ASAM, Model architecture=ResNet502025.06 | 12.667 | |
| NG + ASAMRelearn learning rate=0.003, Attack optimizer (A)=ASAM, Model architecture=ResNet502025.06 | 11.533 | |
| SharpMinMax + ASAMRelearn learning rate=0.003, Attack optimizer (A)=ASAM, Model architecture=ResNet502025.06 | 11.2 | |
| NGRelearn learning rate=0.003, Attack optimizer (A)=SGD, Model architecture=ResNet502025.06 | 11.167 | |
| NG + ASAMRelearn learning rate=0.003, Attack optimizer (A)=SGD, Model architecture=ResNet502025.06 | 11.033 | |
| RLRelearn learning rate=0.004, Attack optimizer (A)=ASAM, Model architecture=ResNet502025.06 | 10.989 | |
| SharpMinMax + ASAMRelearn learning rate=0.003, Attack optimizer (A)=SGD, Model architecture=ResNet502025.06 | 10.667 | |
| NGRelearn learning rate=0.002, Attack optimizer (A)=ASAM, Model architecture=ResNet502025.06 | 10.333 | |
| RLRelearn learning rate=0.004, Attack optimizer (A)=SGD, Model architecture=ResNet502025.06 | 9.622 | |
| RLRelearn learning rate=0.003, Attack optimizer (A)=ASAM, Model architecture=ResNet502025.06 | 9.589 | |
| RL + ASAMRelearn learning rate=0.004, Attack optimizer (A)=ASAM, Model architecture=ResNet502025.06 | 9.467 | |
| NG + ASAMRelearn learning rate=0.002, Attack optimizer (A)=ASAM, Model architecture=ResNet502025.06 | 9.289 | |
| SharpMinMax + ASAMRelearn learning rate=0.002, Attack optimizer (A)=ASAM, Model architecture=ResNet502025.06 | 8.8 | |
| NGRelearn learning rate=0.002, Attack optimizer (A)=SGD, Model architecture=ResNet502025.06 | 8.644 | |
| RLRelearn learning rate=0.002, Attack optimizer (A)=ASAM, Model architecture=ResNet502025.06 | 8.556 | |
| NG + ASAMRelearn learning rate=0.002, Attack optimizer (A)=SGD, Model architecture=ResNet502025.06 | 8.533 | |
| RLRelearn learning rate=0.003, Attack optimizer (A)=SGD, Model architecture=ResNet502025.06 | 8.5 | |
| RL + ASAMRelearn learning rate=0.003, Attack optimizer (A)=ASAM, Model architecture=ResNet502025.06 | 8.489 | |
| RL + ASAMRelearn learning rate=0.004, Attack optimizer (A)=SGD, Model architecture=ResNet502025.06 | 8.367 | |
| SharpMinMax + ASAMRelearn learning rate=0.002, Attack optimizer (A)=SGD, Model architecture=ResNet502025.06 | 8.333 | |
| RL + ASAMRelearn learning rate=0.003, Attack optimizer (A)=SGD, Model architecture=ResNet502025.06 | 7.444 | |
| RL + ASAMRelearn learning rate=0.002, Attack optimizer (A)=ASAM, Model architecture=ResNet502025.06 | 7.378 | |
| RLRelearn learning rate=0.002, Attack optimizer (A)=SGD, Model architecture=ResNet502025.06 | 7.122 | |
| RL + ASAMRelearn learning rate=0.002, Attack optimizer (A)=SGD, Model architecture=ResNet502025.06 | 6.222 |