Re: [mlpack] GSoc 2018 Project Ideas

[Marcus Edel]

Hello Saurav,

thanks for getting in touch.

There is an open discussion on the mailing list:

http://knife.lugatgt.org/pipermail/mlpack/2018-January/003438.html

make sure to look at the answer as well.

> Also, I had few more ideas in my mind. We can also implement few genetic
> algorithms for constrained multiobjective optimization tasks. I would love to
> discuss these ideas with the mentors.

Sounds good, I'm open to discuss further ideas. Either here on the mailing list
or on IRC.

> Where should I start contributing for PSO unconstrained/ constrained
> optimization?

Getting familiar with the codebase especially with the optimization framework is
a good starting point. https://arxiv.org/abs/1711.06581 could be helpful too. If
you like you could implement an nonexisting optimization method, but don't feel
obligated.

I hope anything I said was helpful, let me know if I should clarify anything.

Thanks,
Marcus


> On 12. Feb 2018, at 14:56, Saurav Agarwal  
> wrote:
> 
> Hi,
>I am being really curious about working on the project of PSO constrained 
> and unconstrained optimization and algorithm optimization for mlpack 
> implementation. 
> Also, I had few more ideas in my mind. We can also implement few genetic 
> algorithms for constrained multiobjective optimization tasks. I would love to 
> discuss these ideas with the mentors. 
> Where should I start contributing for PSO unconstrained/ constrained 
> optimization? 
> 
> -- 
> Regards,
> Saurav Agarwal
> 
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> mlpack mailing list
> mlpack@lists.mlpack.org
> http://knife.lugatgt.org/cgi-bin/mailman/listinfo/mlpack

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Re: [mlpack] GSoc 2018 Project Ideas

[Saurav Agarwal]

Hi,
   I am being really curious about working on the project of PSO
constrained and unconstrained optimization and algorithm optimization for
mlpack implementation.
Also, I had few more ideas in my mind. We can also implement few genetic
algorithms for constrained multiobjective optimization tasks. I would love
to discuss these ideas with the mentors.
Where should I start contributing for PSO unconstrained/ constrained
optimization?

-- 
Regards,
Saurav Agarwal
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