[mlpack] GSoc : Parallel Stochastic Optimization Methods - Ideas

[Srinivas Kumar]

Hi Ryan,

My name is Srinivas and I'm a Masters student at the Supercomputer
Education Research Center (India).

I've worked with different frameworks like OpenMP, MPI, Hadoop and CUDA . I
also have good knowledge in C++, JAVA and Python.

I'm interested in the "Parallel Stochastic Optimization Methods" project
that you have offered.

I realized what you are actually looking for is to fine-tune the
implementation of SGD for multi-core rather than extend it to distributed
memory systems.

I came across a paper by  L ́eon Bottou titled "Stochastic Gradient Descent
Tricks"

Link to paper : http://research.microsoft.com/pubs/192769/tricks-2012.pdf
Link to code  : https://github.com/npinto/bottou-sgd

It offers a nice set of recommendations for implementing SGD. I would like
to know if it would be a good idea to use these recommendations to
implement and fine-tune SGD for *mlpack* ?

I would like to work on mlpack as a GSoC project. Please let me know what
you think about this idea.

Thanks in advance.

Srinivas.K

Master's Student,
Department of Computational and Data Science,
Supercomputer Education Research Center,
Indian Institute of Science, India


-- 
its now or never
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