The slides are pretty clear.  The titles of other talks there lead to a good
batch of articles to read.

The basic idea is that sampling rows and/or columns can give approximately
correct matrix products very quickly.  This same technique can be used to
give SVD like results quickly.

I see now that our internal techniques for recommendation analysis use
theoretically similar (but practically quite different) techniques to make
huge graph operations feasible.  I guess we weren't the only ones to think
along these lines.

Here are some URL's:

http://citeseer.ist.psu.edu/drineas01fast.html            *Fast Monte-Carlo
Algorithms for Approximate Matrix Multiplication*
http://citeseer.ist.psu.edu/751036.html                     *An Experimental
Evaluation of a Monte-Carlo* ...
http://citeseer.ist.psu.edu/751131.html                     *A Randomized
Singular Value Decomposition*
http://www.etis.ensea.fr/~wtda/                                *Workshop on
Tensor Decompositions and Applications
*http://citeseer.ist.psu.edu/drineas99clustering.html    *Clustering in
Large Graphs and Matrices*

On Thu, May 22, 2008 at 6:32 PM, Allen Day <[EMAIL PROTECTED]> wrote:

> My bad.  There is audio for some of the talks but not any of the ones
> from that week.
>
> -Allen
>
>
> On Thu, May 22, 2008 at 6:13 PM, Jeff Eastman
> <[EMAIL PROTECTED]> wrote:
> > I found the slides, which look fascinating, but no audio for this
> > presentation. Am I overlooking something?
> > Jeff
> >
> >
> > Allen Day wrote:
> >>
> >> There was an excellent presentation from Rob Fergus on this data set
> >> at last year's UCLA/NSF "Mathematics of Search Engines" workshop.
> >>
> >> https://www.ipam.ucla.edu/schedule.aspx?pc=sews2
> >>
> >> Scroll down to Tuesday 3pm to grab the slides and audio.
> >>
> >> -Allen
> >>
> >>
> >> On Thu, May 22, 2008 at 5:44 PM, Ted Dunning <[EMAIL PROTECTED]>
> >> wrote:
> >>
> >>>
> >>> Here is a source of 1.5 million small (32 x 32) images with English
> >>> labels.
> >>> This might be an interesting large-ish dataset for clustering and
> >>> learning
> >>> experiments.
> >>>
> >>> The total size of the data set is pretty small (only 3+ GB) so it
> >>> shouldn't
> >>> be such a big deal to snag.
> >>>
> >>> http://people.csail.mit.edu/torralba/tinyimages/
> >>>
> >>>
> >>>
> >>> --
> >>> ted
> >>>
> >>>
> >>
> >>
> >>
> >>
> >
> >
>
>
>
> --
> allenday.skype
> +1 (415) 335-4654 (office)
> +1 (310) 804-5304 (mobile)
> +1 (515) 474-9337 (fax)
>



-- 
ted

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