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From 冯伟 <whitepapers...@gmail.com>
Subject About Matrix Factorization and Vector/Matrix Manipulation
Date Thu, 10 May 2012 15:33:44 GMT
I want to look at the distribution implementation of matrix factorization
in Mahout Recommender System. Before I start from
org.apache.mahout.cf.taste.hadoop.als.RecommenderJob,is there any papers /
technical materials for reference? It seems that the parameters are learned
by ALS. Then is there a stochastic gradient descent implementation? I know
GraphLab of CMU for quite a while since KDDCup 2011,is there any comparison
between GraphLab's collaborative filtering lib and Mahout's?

The last question is about vector/matrix manipulation. In Matlab / Octave,
algorithms that employ vector/matrix manipulation are always faster than
their non-vectorized version (iterating elements in vectors and matrix one
by one). It seems that Matlab has employed the some underlining hardware
supported technique (http://en.wikipedia.org/wiki/General_Matrix_Multiply).
Is this technique supported by Mahout too ? Especially for sparse
vector/matrix.
-- 
Wei Feng

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