[mlpack] Fwd: mlpack:GSOC'17

[abhinav kumar]

Hey,
Thank you for reply.
I was going through the mlpack source code and found SGD is already
implemented. So I have to write the implementation of SCD and its code
should be written with OpenMP along with code of SGD ? I have seen there is
OpenMP implementation of LSH search and this ticket number (#179)
<http://www.mlpack.org/trac/ticket/179> is about parallelism of mlpack. Can
you point me to other OpenMP implementation in mlpack so that I can study
them.

I was looking at the Issue 401 <https://github.com/mlpack/mlpack/issues/401> on
github and I thought it is a good starter for me to work on. It will help
me to learn convex optimization and make a contribution to mlpack. I have
some doubt ( or less knowledge ) regarding that how constraints to be
written for that. It would be great if you can point me some resource
regarding that.

Another thing is there any other issue or  work I should look for this
project ?

Thanks,

Abhinav Kumar
NIT Srinagar


On Fri, Feb 10, 2017 at 8:41 PM, Ryan Curtin <ryan at ratml.org> wrote:

> On Fri, Feb 10, 2017 at 12:16:02AM +0530, abhinav kumar wrote:
> > Hello everyone,
> >  Myself Abhinav Kumar, 4th year computer science student from NIT
> Srinagar,
> > India. I am a machine learning and parallel computing enthusiast and
> worked
> > on unsupervised learning during my previous internship. I was learning
> > about ml programing then I came through mlpack. Its a nice and promising
> > software.
> > I have experience of using armadillo,cmake and lapack for my ml and c++
> > programs. I have made contribution to gnome software.
> > I like to contribute to mlpack and be part of GSOC'17 through mlpack
> > organisation. I have compiled mlpack from source on my computer and used
> > some of its algorithm. I am also familiar with git system and have a good
> > experience with c++. I have read about template SFINAE and reading about
> > policy based design (as provided in mlpack documentation).
> >
> > I was going through mlpack GSOC list 2017 and I like to work on -
> >  * Parallel stochastic optimization methods *
> > I am very much interested to work on this project.I have found these
> paper
> > related to this project -
> >  for SCD (https://arxiv.org/pdf/1311.1873.pdf)
> >  for SGD (http://martin.zinkevich.org/publications/nips2010.pdf)
> > I have also found that this project was listed in GSOC 2015 and archive
> > related to this is - Archive March 2015
> > <http://knife.lugatgt.org/pipermail/mlpack/2015-March/001658.html>
> >  For Martin Zinkevich paper, it was commented as
> > " I think it makes more sense in a distributed setting (where
> communication
> > is much more expensive than in a shared memory
> > setting). " So, I have to look for other paper on it.
> > For this project , I need to learn convex optimization and this course by
> > Stanford University
> > <http://online.stanford.edu/course/convex-optimization-winter-2014> can
> be
> > really helpful. If there is any other resources to look for please direct
> > me to that.
> > I have some experience of creating multi-thread program on c# and i think
> > by using that knowledge and studying tutorials based on c++ threads I can
> > do a great work on this project.
> >
> > It would be a great opportunity to be part of this organisation and
> > contribute to mlpack.
>
> Hi Abhinav,
>
> There are several other mailing list threads, but since you have already
> searched the archive, you have probably found them.  An implementation
> should be written with OpenMP to match the rest of the parallel code in
> mlpack, so keep that in mind while you are preparing your plans.
>
> Let me know if there is anything else I can clarify.
>
> Thanks,
>
> Ryan
>
> --
> Ryan Curtin    | "And tell the engineers to wipe that stupid smile
> ryan at ratml.org | off his face this time."  - Lou
>
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