[mlpack] Fwd: Apply for the implementation of the QUIC-SVD collaborative filtering

[Wilson Cao]

Hi Ryan,

Thanks for your reply, and I really appreciate that.

No.  We have arma::mat (and other numerical matrix data types) as data
> types, and if we wanted to start supporting other types of features, it
> takes a lot of overhead and will be slow.  If anything, a transition
> layer to convert non-numeric categorical features into numerical
> features is the way to go.


Thanks, I have check the Armadillo library and now I know that we should
add a layer instead of designing some new API. Thanks for your advice.
Also, I found that in the Armadillo library, the svd() has been
implemented. Is that what we do is to use the QUIC-SVD to improve the
performance of the original SVD?

Since in the past I attended in a cf competition, and the competition data
is not the pure "rate", it is the record of the behavior of the users,like
purchasing, adding to the cart,etc . It seems necessary that we can design
the API to let other programmers to define what their "rate" are in the cf.

I'm sorry, but we can't accept late proposals.  If you upload your
> proposal to Melange (which I think you already have) I will look at it
> and comment.


Thanks for your detailed explanation. I certainly will upload my proposal
to the Melange, I just can't get my hand dirty in the project until next
week because of my exam this Sunday. Without trying to implement the
algorithm, I worry that it would make my proposal very vulnerable. I will
get my hand in the project as soon as I finish the exam.

Again, thanks for your valuable advice!

Yours,

Wilson Cao



On Wed, Mar 19, 2014 at 3:37 AM, Ryan Curtin <gth671b at mail.gatech.edu>wrote:

> On Mon, Mar 17, 2014 at 12:55:50PM +0800, Wilson Cao wrote:
> > Hello,
> >
> > My name is Wilson Cao, a Chinese students from South China University of
> > Technology. I am really interested in the implementation of the QUIC-SVD
> > collaborative filtering.
>
> Hi Wilson,
>
> I'm sorry for the slow response.
>
> > The most important part of this SVD-based collaborative filtering is the
> to
> > implement the svd method to mlpack API. The QUIC-SVD method use the new
> > data structure -- cosine tree. It is more efficient than the previous
> Monte
> > Carlo linear algebra methods.
>
> Efficient in what way?
>
> > What API can we use to implement the QUIC-SVD algorithm? I think maybe we
> > should create the abstract class or the template class, and this class
> > constructor should take the user-item matrix as an input. Also, the
> > collaborative filtering algorithm should be include in the in this class.
> >
> > Sometimes, the rates of the item from the users are not always be the
> > number, so I think we need to implement a kind of API so that the
> > programmer can define the type of "rate".
>
> No.  We have arma::mat (and other numerical matrix data types) as data
> types, and if we wanted to start supporting other types of features, it
> takes a lot of overhead and will be slow.  If anything, a transition
> layer to convert non-numeric categorical features into numerical
> features is the way to go.
>
> > I really believe that the performance is the key to this algorithm, so I
> am
> > wondering if we can use the cluster distributed system to implement is
> > algorithm? I haven't find out whether this is feasible.
>
> If you have any ideas that can balance API cleanliness and simplicity
> with scalability, I'm all ears.  Making trees work in a distributed
> setting is not an easy task, in general.
>
> > I am really interested in the project! However, I have been in the
> trouble
> > that I have my TOEFL exam in Mar 23 (UTC + 8:00), which means that I
> can't
> > get myself full prepared for the proposal. I have to apology for my lack
> > preparation for this project. I am wondering whether I can send the draft
> > proposal first? I promise I will get full prepared for the project and
> show
> > my deep passion on it right after my TOEFL exam.
>
> I'm sorry, but we can't accept late proposals.  If you upload your
> proposal to Melange (which I think you already have) I will look at it
> and comment.
>
> Thanks,
>
> Ryan
>
> --
> Ryan Curtin    | "Sometimes, I doubt your commitment to Sparkle
> ryan at ratml.org | Motion!"  - Kitty Farmer
>
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