[mlpack] GSOC 21

[Omar Shrit]

Hello Oleksandr,

Thank you for you interest in mlpack.

Evolutionary algorithms are welcomed and can be a good project, we
already have several algorithms in ensmallen such as PSO and cmaes.
I do not think that moving cmaes to mlpack would be a good idea. The
objective of ensmallen is to have all optimization methods in one place,
knowing that ensmallen was already part of mlpack.

Rust binding is a good idea too, as GNN. However, non of these ideas is
related to one another, which will make it very hard to create a solid
and consistent GSoC project, knowing that GSoC this year is shorter.
Therefore, I would concentrate on one idea and build a proposal on it,
and try to have some proof of concept in order to make the proposal more
convincing.

Hope you find this helpful.

Thanks,

Omar

On 03/15, Oleksandr Nikolskyy wrote:
> Hi, I am Oleksandr, CS Masters student from Bonn, Germany.
> 
> I was reading about cma es and its extensions(which is one of gsoc ideas)
> and it is really interesting.Found also some additional sources about
> evolution algorithms in general e.g
> https://openai.com/blog/evolution-strategies/
> https://blog.otoro.net/2017/10/29/visual-evolution-strategies/
> Sounds also like the results of evolutional algorithms can be used for some
> RL problems.I would be interested to work on a proposal for GSOC, if this
> topic is still free.Currently, the cma es is living in the ensmallen
> library.If working on this topic, is it a good idea to work towards the
> implementation of cma-es enhancements in the mlpack package? For example to
> enable bindings?
> 
> 
> Also, I had some other ideas:
> 
> 
>    1. Create Rust bindings
>    2. Start mlpack.js, as a ready to use node package
>    3. Add explicit support for graph neural networks to the ann module
>    along with the core module.
> 
> Would be happy about your feedback! :) In the meanwhile, I will continue my
> research on the realizability of these ideas.

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