Is it possible to use multithreading with non negative matrix factorization?
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Are there results about performance and scalability of scikit-learn
implementation of NMF?
According to this thread on SO
http://stackoverflow.com/questions/18575846/non-negative-matrix-factorization-of-sparse-input
There are scalability issue. I would be interested to know the biggest dataset
Hi all,
I'm using GraphLASSO to estimate the graphical model and precision
matrix of my variables. It is well known that GraphLASSO and related
methods are very sensitive to contaminated data and their estimates have
low break-down points:
http://arxiv.org/abs/1501.01219
As suggested by the au