The link seems to be a nice summary presentation of the Yahoo paper, same authors. Nice.
On Tue, Feb 1, 2011 at 1:09 PM, Ted Dunning <[email protected]> wrote: > 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 <[email protected]> > 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 <[email protected]> > 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 <[email protected]> wrote: > > > > > > > That Elkan / Menon paper has an elegant theoretical formulation of a > > > > recommender that uses both ratings and side info at the same time. > > > > > > > > > >
