Hi Deb,
Putting your code on github will be much appreciated -- it will give us a
good starting point to adapt for our purposes.
Regards.
On Sat, Jun 28, 2014 at 10:57 AM, Debasish Das [via Apache Spark Developers
List] wrote:
> Factorization problems are non-convex and so both ALS and DSGD w
Factorization problems are non-convex and so both ALS and DSGD will
converge to local minima and it is not clear which minima will be better
than the other until we run both the algorithms and see...
So I will still say get a DSGD version running in the test setup while you
experiment with the Spa
Hi Deb,
Thanks so much for your response! At this point, we haven't determined
which of DSGD/ALS to go with and were waiting on guidance like yours to
tell us what the right option would be. It looks like ALS seems to be good
enough for our purposes.
Regards.
On Fri, Jun 27, 2014 at 12:47 PM, D
Hi,
In my experiments with Jellyfish I did not see any substantial RMSE loss
over DSGD for Netflix dataset...
So we decided to stick with ALS and implemented a family of Quadratic
Minimization solvers that stays in the ALS realm but can solve interesting
constraints(positivity, bounds, L1, equali
Hi all,
Just found this thread -- is there an update on including DSGD in Spark? We
have a project that entails topic modeling on a document-term matrix using
matrix factorization, and were wondering if we should use ALS or attempt
writing our own matrix factorization implementation on top of Spar
