[mlpack] mlpack:GSOC'17

[abhinav kumar]

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.
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://knife.lugatgt.org/pipermail/mlpack/attachments/20170210/dcde18ab/attachment.html>