No, that should not be the case unless your input is random and k+p << rank(A). However, let me double check what you are saying, maybe something got broken. On Aug 31, 2012 10:28 PM, "Ahmed Elgohary" <[email protected]> wrote:
> Hi, > > I used mahout's stochastic svd implementation to find the singular vectors > and the singular vectors of a small matrix 99x100. Then, I compared the > results to the singular values and the singular vectors obtained using the > svd function in matlab and the single threaded version of the ssvd. I got > pretty much the same singular values using the 3 implementations. however, > the singular vectors of mahout's ssvd were significantly different. I tried > multiple values for the parameters P and Q but, that does not seem to solve > the problem. Does MR implementation of the SSVD do extra approximations > over the single threaded ssvd so their results might not be the same? Any > advice how I can tune mahout's ssvd to get the same singular vectors of the > single threaded ssvd? > > thanks, > > --ahmed >
