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

new datasets/ noisy instances #15

Open
nazaretl opened this issue May 9, 2022 · 1 comment
Open

new datasets/ noisy instances #15

nazaretl opened this issue May 9, 2022 · 1 comment

Comments

@nazaretl
Copy link

nazaretl commented May 9, 2022

Hi,
thanks for sharing your implementation. I have two questions about it:

  1. Is the code tailored to the datasets used in the paper or can one apply it to any data?
  2. Is it possible to identify the noisy instances (return the noisy IDs or the clean set)?

Thanks!

@Newbeeer
Copy link
Owner

Hi,

Sorry for the huge delay. The code works for general dataset. Our method does not have the capability for idetifying the clean set. However, we prove that training with DMI loss on noisy label is equivalent to vanilla ERM on clean set.

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