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correct application of nuclear norm in benchmarking
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(1) I fixed a few issues with the nuclear norm implementation, e.g., the original code won't work in the 1-dim case (because the parameter is passed as a 0-dim vector).
(2) I revised the penalty calc…
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Currently it seems like this
OLS linear -> ridge regression -> lasso regression -> elasticnet regression -> nuclear norm regularization
but what is nuclear norm regularization?
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A simple problem:
```julia
using Convex;
using ECOS;
numRows = 200; #
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Currently PyTorch has a spectral matrix norm implementation based on power iteration hidden inside the SpectralNorm. Since new `torch.norm` supports matrix norms (e.g. nuclear norm), it may be good to…
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PR #48436 broke some of the extreme value behavior for `linalg.norm`, when`svd` is called internally: https://github.com/pytorch/pytorch/pull/48436#issuecomment-741149670
cc @ezyang @gchanan @zou3519…
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Hey! Out of curiosity, what is the limitation that prevents `imate` from working with products of rectangular matrices?
For any real-valued matrix $A \in \mathbb{R}^{n \times m}$ and positive semi-…
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Hello, is your code suitable for calculating the nuclear norm loss between tensor (batch, channel, height, width)?
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should weight norm include p=, that is option to change p to nuclear, 3, or higher value?
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There is already support for BilinearOperator in `pyproximal/pyproximal/utils/bilinear.py` and the PALM optimizer; however,
they do not scale to second-order methods such as Levenberg-Marquardt (LM) …