I am working on matrix factorization and I read the the paper
http://arxiv.org/abs/0909.4061 about random projections. I am implementing
distributed NMF.   I tried to understand work of Dimitry Liubimov
https://issues.apache.org/jira/browse/MAHOUT-376 about SSVD I think it is
very relevant in the part where he pre process the matrix before starting
the decomposition. Could anybody help me pre process the input matrix to
produce a smaller one after doing the random projections to decrease its
size. Also how could i map back the results from the decomposed matrices to
the real data since they will be in another space. Is there a class in
Mahout that i can use that will do that. 
Regards
Ahmed Nagy

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Ahmed Nagy
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