Gradient descent is a good solution for approximate SVD, I'm using it as part of my data mining final project (working on the netflix prize). I'm using this guy's code: http://www.timelydevelopment.com/demos/NetflixPrize.aspx, modified to print out the singular vectors when it finishes. It took about 32 hours (can't quite remember) to find the first 64 singular values* on the netflix dataset (480000x18000, 1.2% non-zero (or is it 1.8%?)) using a 2.2GHz Opteron and ~2 gigs of ram.
I'm sure there are better methods, but this one is easy and is producing great results. If you have any questions, you can shoot me an email at sbuss at cise dot ufl dot edu.
As for hadoop, I don't know of any parallel implementations of this that exist, but I don't think it would be /too/ hard to parallelize the gradient descent approach. Just split up the error calculation into several smaller chunks. If you get it running in parallel, let me know.
*edit: changed "vectors" to "values" in first paragraph.
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Gradient descent is a good solution for approximate SVD, I'm using it as part of my data mining final project (working on the netflix prize). I'm using this guy's code: http://www.timelydevelopment.com/demos/NetflixPrize.aspx, modified to print out the singular vectors when it finishes. It took about 32 hours (can't quite remember) to find the first 64 singular values* on the netflix dataset (480000x18000, 1.2% non-zero (or is it 1.8%?)) using a 2.2GHz Opteron and ~2 gigs of ram.
I'm sure there are better methods, but this one is easy and is producing great results. If you have any questions, you can shoot me an email at sbuss at cise dot ufl dot edu.
As for hadoop, I don't know of any parallel implementations of this that exist, but I don't think it would be /too/ hard to parallelize the gradient descent approach. Just split up the error calculation into several smaller chunks. If you get it running in parallel, let me know.
*edit: changed "vectors" to "values" in first paragraph.
Thanks for the link - these results are encouraging. I'll think about it - if I come up with anything I'll let you know. Good luck.