Hi Aureliano,
Will it be possible for you to give the test-case ? You can add it to JIRA
as well as an attachment I guess...
I am preparing the PR for ADMM based QuadraticMinimizer...In my matlab
experiments with scaling the rank to 1000 and beyond (which is too high for
ALS but gives a good
It is possible that the answer (the final solution vector x) given by two
different algorithms (such as the one in mllib and in R) are different, as
the problem may not be strictly convex and multiple global optimum may
exist. However, these answers should admit the same objective values. Can
you
Hi,
The recently added NNLS implementation in MLlib returns wrong solutions.
This is not data specific, just try any data in R's nnls, and then the same
data in MLlib's NNLS. The results are very different.
Also, the elected algorithm Polyak(1969) is not the best one around. The
most popular one
