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

The introduction part is so weird #9

Open
LoveMiki opened this issue Jun 28, 2021 · 0 comments
Open

The introduction part is so weird #9

LoveMiki opened this issue Jun 28, 2021 · 0 comments

Comments

@LoveMiki
Copy link

First of all, thanks for the interesting work. The experimental results are still competitive to the current SOTA works.
However, the introduction makes me confused and doubt the results. For example, in paragraph 3, you mentioned 'Prior studies suggest that using meta-learning outperformes "vanilla" nearest neighbor classification [26, 30]'. In fact, references 26 and 30 were exactly the methods that used meta-learning, as they tackled the FSL problem within a meta-learning setting. Also, in paragraph 4, you mentioned that your method achieve SOTA performance without using meta-learning, which is the weirdest part because you were already using meta-learning when you used N-way K-shot setting.

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

1 participant