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

[Wilson Cao]

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.

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.

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".

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.

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 am looking forward to your reply and suggestions.

Yours,

Wilson Cao
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