[mlpack] Collaborative filtering - GSOC project idea

[Haritha Sreedharan Nair]

Hi,
I am Haritha Sreedharan Nair (github username- haritha1313).
I would like to work on implementing better collaborative filtering models
in mlpack as part of GSOC. I had worked on recommendation system based
projects earlier and I see a lot of scope in mlpack's CF implementation.

As of now I have been through the research paper cited in mlpack/methods/cf
and realized that some concepts mentioned in the paper (the ones explaining
how to handle biases etc.) haven't been implemented yet. I have also
explored a few other research papers and articles including the one
mentioned in mlpack's ideas wiki.

I found this (https://www.comp.nus.edu.sg/~xiangnan/papers/ncf.pdf) paper
interesting - it gives importance to implicit feedback, performs better
than existing methods and it is able to generalize the matrix factorization
methods we use in mlpack too. Since it is a pretty new research paper I am
not able to find any discussions on it and would like to know if the
maintainers find it to be worth implementing.

I would also like to clarify a doubt. Is there any reason why quic_svd and
randomized_svd have not been used for matrix factorization in CF?

Thank you.
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