The divide and conquer approach sounds promising; along those lines I have heard things about non-negative matrix factorization being worth doing since there are methods to break the matrix into parts and then combine the result after processing.
http://en.wikipedia.org/wiki/Non-negative_matrix_factorization http://www.cs.helsinki.fi/u/phoyer/papers/pdf/NMFscweb.pdf On Sun, Sep 8, 2013 at 8:47 PM, Dmitriy Lyubimov <[email protected]> wrote: > i used to really drool over papers like this :) > > On Sun, Sep 8, 2013 at 4:39 PM, Ted Dunning <[email protected]> wrote: > > http://arxiv.org/pdf/1107.0789v6.pdf > > > > The basic idea is to use randomized column sampling to divide the matrix > > into parts which are then decomposed using whatever method de jour you > > like. The decompositions of the parts can then be put back together to > get > > a good estimate of the decomposition of the original matrix. > > > > Combined row and column decomposition can also be used and I think > > extension to row sampling (more convenient for us) is relatively trivial. >
