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

paper review #37

Open
KBodolai opened this issue Aug 25, 2024 · 2 comments
Open

paper review #37

KBodolai opened this issue Aug 25, 2024 · 2 comments

Comments

@KBodolai
Copy link

Hello, I think you've done a great job at context-setting, and a fantastic work of pulling all of these algorithms together in one single, consistent API. On top of that, the docs are delightful.

a few minor things from the paper review, relating to openjournals/joss-reviews#6507:

  1. Minor typo in the second paragraph of the statement of need: ``arms". is started with a double backtick and finishes with double quotes.
  2. Just after that, I believe there's a missing "be": just before "infeasible" in the following statement Therefore, directly applying multi-armed bandit algorithms to such problems would infeasible
  3. The Quick Example section in the Readme could be made a bit more specific and self-evident by including the specific imports used in it.
  4. Love the real world example - if I were to add anything here, it would be a comparison with other algorithms commonly used for hyperparameter tuning (time, optimality)

Overall fantastic job, well done!

@KBodolai
Copy link
Author

@WilliamLwj , happy to work on a small PR for point 4 if you want!

@WilliamLwj
Copy link
Owner

Hi, thank you for the review! We've updated the repository and the document. Please find the details here

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