[mlpack] GSOC 18 [Mlpack] : Reinforcement learning

[Marcus Edel]

Hello Rohan,

thanks for getting in touch.

> I have a good knowledge in neural networks and deep learning.Previous summer, I
> did my summer internship at Beckmann Institute, UIUC (University of Illinois at
> Urbana-Champaign), USA on deep learning in cancer imaging.

That sounds really interesting, would be awesome if Deep learning would have an
positive impact on this important problem, I think you used some CNN flavor in
your experiments?

> Previous semester , I took Computer Vision using machine learning course at my
> college. I proposed a transfer learning architecture for semantic segmentation
> in deep learning as a semester project. The codes can be found here.

This looks really interesting as well, note Theano is somewhat different from
what we usally do at mlpack.

> Presently I am going through the code structure of mlpack. I am comfortable with
> the software because I have good background in C++. Since there are none tickets
> open presently, I am currently following Marcus's suggestion to go through the
> code base and try to improve the codes. I will be grateful to any member who
> would like to provide any suggestions.

Another idea is to implement a simple RL method like (stochastic) Policy
Gradients and test it on the existing environments, but don't feel obligated.

Let me know if I should clarify anything.

Thanks,
Marcus


> On 16. Feb 2018, at 07:29, Rohan Raj <rajrohan1108 at gmail.com> wrote:
> 
> Hello Everyone,
> 
> I am Rohan Raj , a pre-final year undergraduate student from IIT Guwahati.
> 
> I am doing my undergraduate research in artificial intelligence , focusing in deep reinforcement learning. Recently, I have submitted my research work, 'Weighted Experience Replay for Independent Q Learning in Multi-Agent Reinforcement Learning' , in ICML 2018 . 
> 
> I have a good knowledge in neural networks and deep learning.Previous summer, I did my summer internship at Beckmann Institute, UIUC (University of Illinois at Urbana-Champaign), USA on deep learning in cancer imaging.
> 
> Previous semester , I took Computer Vision using machine learning course at my college. I proposed a transfer learning architecture for semantic segmentation in deep learning as a semester project. The codes can be found here <https://github.com/luffy1996/transfer-learning-semantic-segmentation>.   
> 
> My blogs are regularly followed by various researchers in the world. You may like to read my introductory blogs on LSTMs <https://rohanrajblogs.blogspot.in/2016/12/writing-simple-lstm-model-on-keras.html> and supercomputer param isham <https://rohanrajblogs.blogspot.in/2017/01/supercomputer-param-ishan.html>.
> 
> I have been through the idea list and I am interested in working in reinforcement learning module. I have sufficient knowledge of DDQN networks and actor-critic networks. I have fairly good understanding of the PPO algorithms.
> 
> Presently I am going through the code structure of mlpack. I am comfortable with the software because I have good background in C++. Since there are none tickets open presently, I am currently following Marcus's suggestion to go through the code base and try to improve the codes. I will be grateful to any member who would like to provide any suggestions. 
> 
> You may want to have a look at my resume, which is attached with this email.
> 
> Thank You,
> Rohan Raj
> Indian Institute of Technology Guwahati
> Assam , India
> Phone : +91 8723990557.
> 
> 
> 
> ᐧ
> <rohanraj_IIT_Guwahati_.pdf>

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