Just to note that in the databricks blog they state that they compute the
top-5 singular vectors, not all singular values/vectors. Computing all is
much more computational intense.
Am 09.08.2017 15:19 schrieb "Jose Francisco Saray Villamizar" <
I am trying to invert a 5000 x 5000 Dense Matrix (99% non-zeros), by using
SVD with an approach simmilar to :
The time Im getting with SVD is close to 10 minutes what is very long for
A benchmark for SVD is already given here
However, it seems they are using sparse matrices, thats why they get short
Have anyone of you try to perform a SVD on a very dense big matrix . ?
Is this time normal ?
Buen dia, alegria !!
José Francisco Saray Villamizar
cel +33 6 13710693 <+33%206%2013%2071%2006%2093>