Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Add Adversarial Training with Early Stopping (ATES), CIFAR-100 #22

Closed
chawins opened this issue Sep 30, 2020 · 2 comments
Closed

Add Adversarial Training with Early Stopping (ATES), CIFAR-100 #22

chawins opened this issue Sep 30, 2020 · 2 comments

Comments

@chawins
Copy link

chawins commented Sep 30, 2020

Paper: Improving Adversarial Robustness Through Progressive Hardening https://arxiv.org/abs/2003.09347

Venue: under review

Dataset and threat model: CIFAR-100, L-inf, 8/255

Code: https://github.com/chawins/ates-minimal

Pre-trained model: weight

Log file: log

Additional data: no

Clean and robust accuracy: 62.82/24.57

Architecture: WRN-34-10

Description of the model/defense: We use the curriculum learning framework to schedule the "difficulty" of adversarial examples generated during adversarial training. This improves both clean and robust accuracy.

@fra31
Copy link
Owner

fra31 commented Oct 1, 2020

Hi,

thanks for the submission! I could reproduce the results you report and I'm happy to add you model!

@chawins
Copy link
Author

chawins commented Oct 2, 2020

Thank you!

@chawins chawins closed this as completed Oct 2, 2020
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests

2 participants