[mlpack] GSOC 2014: collaborative filtering package improvements

[Mudit Gupta]

Hi,

Thank you for your mail. I have modified the project wiki accordingly.

A part of QUIC-SVD has been implemented. You can check out the cosine tree
implementation here
https://trac.research.cc.gatech.edu/fastlab/browser/tags/mlpack-1.0.8/src/mlpack/core/tree/cosine_tree?rev=16133.
In QUIC-SVD you have to construct the cosine tree first before SVD. Please
go though the paper for details.

You can discuss the algorithms which you plan to implement and how would
you architect the solution. You can look into extending the executable for
cf but I think Ryan and Ajinkya would be able to guide you on this.

Best,

Mudit Raj Gupta




On Wed, Mar 12, 2014 at 11:57 AM, Pulkit Yadav <yadavpulkit at gmail.com>wrote:

> Hello,
>
> I am Pulkit Yadav, a senior year Computer Science and Engineering
> undergraduate at IIT Delhi. I am passionate for Machine Learning and have
> also taken relevant courses like Machine Learning, Artificial Neural
> Networks, Artificial Intelligence, etc. at my university. Having done a
> large number of projects in C++, I am quite proficient in the language. I
> have also been actively involved in research projects and have two
> publications to my name. So, reading latest literature on efficient
> algorithms for implementation would not be an issue.
>
> I am very excited in contributing to mlpack library. I am particularly
> interested in the project idea "collaborative filtering package
> improvements" and would like to work on it.
>
> The project ideas page (http://www.mlpack.org/trac/wiki/SummerOfCodeIdeas)
> says that QUIC-SVD needs to be implemented. However the project wiki (
> http://www.mlpack.org/trac/wiki/cf) says that QUIC-SVD using cosine trees
> has already been implemented. Could you please clarify which algorithms
> have been implemented and what are some suggestions for implementation?
>
> I have installed mlpack and tried the cf module. Currently, I am studying
> the source code of cf module and the tree abstractions
> (src/mlpack/core/tree/).
>
> How can I start contributing to the project now in some way? Kindly give
> suggestions how should I proceed from here.
>
> Thanks,
> Pulkit
>
>
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>
>
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