- The code to replicate the experimental results presented in the paper Adversarial Machine Unlearning)
- Install needed packages:
conda env create -f environment.yml - Install an old version of pytorch:
conda install pytorch==2.2.2 torchvision==0.17.2 torchaudio==2.2.2 pytorch-cuda=11.8 -c pytorch -c nvidia - CIFAR-10 random forgetting:
cd src/; chmod +x cifar10_random_forgetting.sh; ./cifar10_random_forgetting.sh 0, where0is the GPU id. - CIFAR-100 random forgetting:
cd src/; chmod +x cifar100_random_forgetting.sh; ./cifar100_random_forgetting.sh 0.
-
Notifications
You must be signed in to change notification settings - Fork 0
The code to replicate the experiments in the paper "Adversarial Machine Unlearning".
marsplus/SG-Unlearn
Folders and files
| Name | Name | Last commit message | Last commit date | |
|---|---|---|---|---|
Repository files navigation
About
The code to replicate the experiments in the paper "Adversarial Machine Unlearning".
Resources
Stars
Watchers
Forks
Releases
No releases published
Packages 0
No packages published