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https://issues.apache.org/jira/browse/MAHOUT-376?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12965598#action_12965598
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Ted Dunning commented on MAHOUT-376:
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{quote}
Ted, sorry i kind of polluted your issue here. Thank you for your encouragement
and help. i probably should've opened another issue once it was clear it
diverged far enough, instead of keep putting stuff here.
{quote}
You didn't pollute anything at all. You contributed a bunch of code here.
So far, the only thing that I worry about is the mixture of array and matrices,
but even that might be fine.
I was dubious of the scalability of the streaming QR, but if that works then we
should be good to go with very little more work.
Do you have any idea if this will work for large sparse matrices as opposed to
the 100K x 100 matrix you are using?
> Implement Map-reduce version of stochastic SVD
> ----------------------------------------------
>
> Key: MAHOUT-376
> URL: https://issues.apache.org/jira/browse/MAHOUT-376
> Project: Mahout
> Issue Type: Improvement
> Components: Math
> Reporter: Ted Dunning
> Assignee: Ted Dunning
> Fix For: 0.5
>
> Attachments: MAHOUT-376.patch, Modified stochastic svd algorithm for
> mapreduce.pdf, QR decomposition for Map.pdf, QR decomposition for Map.pdf, QR
> decomposition for Map.pdf, sd-bib.bib, sd.pdf, sd.pdf, sd.pdf, sd.pdf,
> sd.tex, sd.tex, sd.tex, sd.tex, SSVD working notes.pdf, SSVD working
> notes.pdf, SSVD working notes.pdf, ssvd-CDH3-or-0.21.patch.gz,
> ssvd-m1.patch.gz, ssvd-m2.patch.gz, ssvd-m3.patch.gz, Stochastic SVD using
> eigensolver trick.pdf
>
>
> See attached pdf for outline of proposed method.
> All comments are welcome.
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