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As you can see the loss of the numpy least-squares solution is much smaller. The two solutions alpha_yaglm and alpha_np are approximately identical up to the first two decimals though. Maybe the yaglm solver terminates too early?
The text was updated successfully, but these errors were encountered:
I found the problem: The FISTA solver indeed stopped to early. Manually setting the maximum iterations to 10 000 instead of the default 1000 and the tolerance to 1e-10 instead of the default 1e-5 produces the correct solution.
Maybe the default parameters could be changed such that simple problems like this are solved correctly by default.
I found that the solution calculated by Glm is not correct. (Or am I using it wrong?) Here is an example of a simple least-squares problem:
As you can see the loss of the numpy least-squares solution is much smaller. The two solutions
alpha_yaglm
andalpha_np
are approximately identical up to the first two decimals though. Maybe the yaglm solver terminates too early?The text was updated successfully, but these errors were encountered: