Some Questions about loss_reweighting.py

[believewhat]

Hello, author, in the cov function of loss_reweighting.py. I think there is a little different with the definition in the paper:
Your code: cov = torch.matmul((w * x).t(), x)
Your paper:

Why the code is not cov = torch.matmul((w * x).t(), w * x)
Thank you very much.

[allenwang2333]

I'm also very confused at that part. The cov in code is calculating the covariance not of the projection to RFF space, but the original space. I think that u and v here means projection to the RFF space.

[zmcwsd]

i think you are right,i agree

[TianmingXie]

I think the authors calculate the covariance matrix through Cov(X, Y)=E(XY)-E(X)E(Y), but not following the formula in the paper.

[gittea-rpi]

The equation in the paper is incorrect, the one used in the code is correct. Cov_w(X,Y) = E_w(XY^T) - E_w(X)E_w(Y)^T, which is computed in the code. (E_w here means the weighted expectation).