-
**Describe the bug**
I was testing abess on the multitask learning problem below (deconvolution of a multichannel signal using a known point spread function / blur kernel by regressing the multichann…
-
In glmnet it is possible to specify box constraints or nonnegativity constraints on the fitted coefficients using the lower.limits and upper.limits argument. I was wondering if it would be hard to inc…
-
Would be nice to support the nonnegative double SVD as intialization in glrm's, especially under nonnegativity constraints:
http://d-kitamura.net/programs/NNDSVD.m
http://www.sciencedirect.com/scien…
-
Just wondering if it would be possible to support an extra argument weights with observation weights? Right now I can fit an `L0Learn `model with observation weights by multiplying both my covariate m…
-
Would you see any possibility to support box constraints on the fitted coefficients, similar to what can be achieved with lower.limits and upper.limits in glmnet?
-
Are there any examples of the use of the exponential cone functionality from matlab I am finding it tricky to get the formulation correct?
-
Thanks for great package - I was wondering if it would also be possible to support sparse covariate matrices, i.e. matrices of class `dgCMatrix `(where `x` is first made sparse using
```
library(Ma…
-
Was just testing glum, but ran into a problem where a glum LASSO fit does not appear to finish (or if it does extremely slowly). The data I simulated was a spike train blurred with a Gaussian point sp…
-
1. An explicit penalty (e.g. L^1) as part of the likelihood
2. Shrinkage, Bayesian style (e.g. [this post](http://bayesiancook.blogspot.fr/2014/02/soft-and-hard-shrinkage.html))
3. Adding parameters o…
-
The gist of the issue is that at one point in my network in my project I feed positive float32 inputs `X` and `W` into a 1d (or 2d) convolution, but unexpectedly obtain explicitly negative outputs.
…