Hello Rohan, welcome to the community.
> I was a computer vision intern at Caterpillar Inc. As part of the machine > learning course, a competition was organized among the students and i have > secured 1st place in that competition I am familiar with deep learning and > have > completed the fast.ai MOOC course along with course offered at our Institute. That sounds really cool, what kind of competition was that? > I have compiled mlpack from source and an looking at the code structure of the > reinforcement learning module. I am unable to find any tickets presently and > hoping that someone could direct me as to how to proceed. One idea is to implement a simple RL method, see the open discussion on the mailing list archive for further guidance and ideas. > Implement latest work(s) in multi-agent reinforcement learning algorithm > Implement Recurrent reinforcement learning algorithm(s) that capture temporal > nature of the environment. Modifications can be made to existing work. I would > like to hear suggestions from mentors what they feel about the idea suggested > and if it seems like an acceptable project to suggest for GSOC. The idea sounds interesting, do you have some particular methods/papers in mind you like to work on since the methods listed on the ideas page are just suggestions this is could be a GSoC project. Let me know if I should clarify anything. Thanks, Marcus > On 20. Feb 2018, at 19:05, ROHAN SAPHAL <[email protected]> wrote: > > Hi, > > I am Rohan Saphal, a pre-final year undergraduate from Indian Institute of > Technology Madras. > > My research interest is in Artificial Intelligence and specifically in Deep > reinforcement learning. > I have been working with Prof. Balaraman Ravindran > <https://scholar.google.co.in/citations?user=nGUcGrYAAAAJ&hl=en> in > Multi-agent reinforcement learning and will continue to do my final degree > thesis project under his guidance. > I am currently a graduate research intern at Intel labs working on > Reinforcement learning. > Previously, I was a computer vision intern at Caterpillar Inc. As part of the > machine learning course, a competition was organized among the students and > i have secured 1st place in that competition > <https://www.kaggle.com/c/iitm-cs4011/leaderboard> > I am familiar with deep learning and have completed the fast.ai > <http://fast.ai/> MOOC course along with course offered at our Institute. > > I have read the papers related to the the reinforcement learning algorithms > mentioned in the ideas page. I am interested to work in the reinforcement > learning module. > > I have compiled mlpack from source and an looking at the code structure of > the reinforcement learning module. I am unable to find any tickets presently > and hoping that someone could direct me as to how to proceed. > > I have been interested to use reinforcement learning for equity trading and > recurrent reinforcement learning algorithms has interested me. I believe the > stock market is a good environment (POMDP) to test and evaluate the > performance of such algorithms as it is a highly challenging setting. There > are so many agents that are involved in the environment and i feel to develop > reinforcement learning algorithms that could trade efficiently in such a > setting will be an interesting problem.Deep learning algorithms like LSTM, > cannot capture the latency involved in the system and hence cannot make real > time predictions. Reinforcement learning algorithms could however learn how > to interact under the latency constraint to make real time predictions. Some > areas that i see work in this area is to: > Implement latest work(s) in multi-agent reinforcement learning algorithm > Implement Recurrent reinforcement learning algorithm(s) that capture temporal > nature of the environment. Modifications can be made to existing work. > I would like to hear suggestions from mentors what they feel about the idea > suggested and if it seems like an acceptable project to suggest for GSOC. > > Thanks for your time > > Hope to hear from you soon. Feel free to ask for any more details about me or > my work. > > Regards, > > Rohan Saphal > > _______________________________________________ > mlpack mailing list > [email protected] > http://knife.lugatgt.org/cgi-bin/mailman/listinfo/mlpack
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