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View Code? Open in Web Editor NEWHyperbolic Busemann Learning with Ideal Prototypes, NeurIPS2021
Home Page: https://minaghadimi.github.io/papers/HBL/index.html
Hyperbolic Busemann Learning with Ideal Prototypes, NeurIPS2021
Home Page: https://minaghadimi.github.io/papers/HBL/index.html
Hi!
I was wondering what is the LR decay setting used for the CUB training runs in the paper?
LR decay was used in CIFAR10 and CIFAR100 for epochs 1000 and 1100; but there are no informations about the decay setting for CUB.
I tried using a decay at epochs 2000 and 2100 and the accuracy seemed better than what was reported in the paper (Test accuracy at 53.54% for dim=50 and 41.8% at dim=3).
Thank you for the great paper!
The code may be inconsistent with the article. Did I overlook something? Thanks.
The paper has said that
"The prototypes are positioned before training and remain fixed, hence the backpropagation only needs to be done with respect to the inputs."
but in the code, there is
target = torch.autograd.Variable(target).cuda()
https://github.com/MinaGhadimiAtigh/Hyperbolic-Busemann-Learning/blob/b2d56e8a935b8f8fa107981d58f5db772981b4cd/HBL.py#L29C9-L29C56
Very interesting paper. Can't wait to see the code. Really curious about the implementation details!
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