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From Ted Dunning <ted.dunn...@gmail.com>
Subject Re: Recommeding on Dynamic Content
Date Tue, 01 Feb 2011 21:09:49 GMT
This looks (based on the first page) very similar to the Menon and Elkan
paper.

Note that parallel != fast.  The LLL implementation of Menon and Elkan
reportedly munches all of netFlix in about 8 minutes if I remember
correctly.  Most batch update gradient methods are highly parallelizable,
but are slower even after parallelization than sequential SGD
implementations.  In Mahout on the relatively small 20 newsgroups, SGD is
faster than anything else we have.  This applies to pretty large problem
sizes (10's of millions of training examples after stratified down-sampling,
billions before).

Conversely, just because SGD isn't normally parallelized, doesn't mean it
can't be.  See here for a counter-example:
http://www.ideal.ece.utexas.edu/seminar/LatentFactorModels.pdf  (thanks to
Isabel for hooking me up with Markus)

On Tue, Feb 1, 2011 at 12:27 PM, Dmitriy Lyubimov <dlieu.7@gmail.com> wrote:

> There's also a paper from Yahoo! research "Regression-based Latent Factor
> Models" http://portal.acm.org/citation.cfm?id=1557029
>
> What i like about this is that it doesn't focus on a particular method to
> combine the models to regress on static profile data + side info. I think
> it
> might be combined with methods ALS-WS  which unlke SGD are
> hadoop-parallelizable to do stage computations. It also serves pretty good
> in situations when there are dyadic interactions but different types
> interaction context (side info) are available (or sometimes none at all)
> but
> static profile information is always available. I think we'll have to get
> on
> this problem pretty soon .
>
>
> On Tue, Feb 1, 2011 at 8:24 AM, Ted Dunning <ted.dunning@gmail.com> wrote:
>
> > And the Mahout-525 github branch of mahout that I started has an
> apparently
> > working version for this algorithm.
> >
> > I would love to support anyone who wants to do last mile work on that
> > stuff.
> >
> > See https://issues.apache.org/jira/browse/MAHOUT-525 for more info
> >
> > On Tue, Feb 1, 2011 at 1:52 AM, Sean Owen <srowen@gmail.com> wrote:
> >
> > > That Elkan / Menon paper has an elegant theoretical formulation of a
> > > recommender that uses both ratings and side info at the same time.
> > >
> >
>

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