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< mjscott>
rcurtin: in response to the sparse SVD stuff, I can't guarantee that all rows/columns have entries
< mjscott>
however, the density of W and H is about the same as V. Like, it is simply not training properly I think, and I'm not sure why. I'm using the SparseSVDCompleteIncrementalLearner, since gradient descent will be faster than alternating. Even though the residue goes to 1e-5, All of the predictions are about the same.
< mjscott>
like, all of the entries in V are in the range 1-5, however, when I factor V with rank 100, I do dot(W.row(i), H.col(j)) for prediction of V(i, j), and for every prediction I get around 20-23, which is way over the range of the entries in V.