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https://issues.apache.org/jira/browse/MAHOUT-1272?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13701244#comment-13701244
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Sebastian Schelter commented on MAHOUT-1272:
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Hello Peng,
the code looks very good on a first glimpse. I'd like you to work on it a
little more though. Can you format the files according to our code conventions
(e.g. no tabs, 2 spaces indent, no braces on next line etc). The code
conventions are basically Oracle's standard conventions with 120 chars per line
instead of 80.
Furthermore, could you benchmark your code via a holdout test on a known
dataset, maybe movielens1M or movielens10M? That would be awesome. I think this
is going to be a great contribution.
> Parallel SGD matrix factorizer for SVDrecommender
> -------------------------------------------------
>
> Key: MAHOUT-1272
> URL: https://issues.apache.org/jira/browse/MAHOUT-1272
> Project: Mahout
> Issue Type: New Feature
> Components: Collaborative Filtering
> Reporter: Peng Cheng
> Assignee: Sean Owen
> Labels: features, patch, test
> Attachments: mahout.patch, ParallelSGDFactorizer.java,
> ParallelSGDFactorizerTest.java
>
> Original Estimate: 336h
> Remaining Estimate: 336h
>
> a parallel factorizer based on MAHOUT-1089 may achieve better performance on
> multicore processor.
> existing code is single-thread and perhaps may still be outperformed by the
> default ALS-WR.
> In addition, its hardcoded online-to-batch-conversion prevents it to be used
> by an online recommender. An online SGD implementation may help build
> high-performance online recommender as a replacement of the outdated
> slope-one.
> The new factorizer can implement either DSGD
> (http://www.mpi-inf.mpg.de/~rgemulla/publications/gemulla11dsgd.pdf) or
> hogwild! (www.cs.wisc.edu/~brecht/papers/hogwildTR.pdf).
> Related discussion has been carried on for a while but remain inconclusive:
> http://web.archiveorange.com/archive/v/z6zxQUSahofuPKEzZkzl
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