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Posted to dev@mahout.apache.org by "Ted Dunning (Reopened) (JIRA)" <ji...@apache.org> on 2012/01/10 14:44:39 UTC
[jira] [Reopened] (MAHOUT-792) Add new stochastic decomposition
code
[ https://issues.apache.org/jira/browse/MAHOUT-792?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Ted Dunning reopened MAHOUT-792:
--------------------------------
I don't think that this issue should have been closed.
> Add new stochastic decomposition code
> -------------------------------------
>
> Key: MAHOUT-792
> URL: https://issues.apache.org/jira/browse/MAHOUT-792
> Project: Mahout
> Issue Type: New Feature
> Reporter: Ted Dunning
> Assignee: Ted Dunning
> Fix For: 0.6
>
> Attachments: MAHOUT-792.patch, MAHOUT-792.patch, sd-2.pdf
>
>
> I have figured out some simplification for our SSVD algorithms. This eliminates the QR decomposition and makes life easier.
> I will produce a patch that contains the following:
> - a CholeskyDecomposition implementation that does pivoting (and thus rank-revealing) or not. This should actually be useful for solution of large out-of-core least squares problems.
> - an in-memory SSVD implementation that should work for matrices up to about 1/3 of available memory.
> - an out-of-core SSVD threaded implementation that should work for very large matrices. It should take time about equal to the cost of reading the input matrix 4 times and will require working disk roughly equal to the size of the input.
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