Hello Xiaohong, we've updated the RL idea, you are welcome to propose different methods that aren't listed.
Thanks, Marcus > On 2. Feb 2019, at 14:46, problemset <[email protected]> wrote: > > > Hi, Manish, > > Great to know more idea will be added to the idealist. I definitely will try > to add more cutting-edge RL techniques. I plan to write a proposal for those > techniques. It will be completed soon. > > Regards, > Xiaohong > > > > At 2019-02-01 11:29:06, "Manish Kumar" <[email protected]> wrote: > Hi Xiaohong, > > It's good to see some novel techniques being added to mlpack's RL framework. > Thanks for working over PER, I am confident that it will be ready to merge > soon enough. > > Regarding GSoC idealist, we are working over adding some recent RL ideas. We > will update the list very soon. You may also propose any idea, you belive > could be a good addition. > > Regards, > Manish Kunar > > > > On Fri, 1 Feb 2019, 07:33 problemset, <[email protected] > <mailto:[email protected]>> wrote: > Hello, everyone, > > I am Xiaohong Ji, undergraduate student from Wuhan University. My research > interest is machine learning and deep reinforcement learning, so I am > interested in project reinforcement learning. My first greeting email was > received a warmful response from this great community. I am writing this > email is that I wish I can apply the GSOC 2019 and look for a potential > mentor. :) > > Currently, I am implementing the PER project > <https://github.com/mlpack/mlpack/pull/1614>. I finished all the > functionality and Manish Kumar's code review. I want to go further. I saw the > updated Idealist and found that there are many new interesting projects. I am > wondering, If we want to apply GSOC 2019 in the mlpack community, can we > pick some reinforcement learning project like GSOC 2018 idealist or focus on > those project provided in the idealist? Other deep learning methods are also > attractive to me, but I wish I can go further in the reinforcement learning > part. > > Thanks, > Xiaohong > > > > > _______________________________________________ > mlpack mailing list > [email protected] <mailto:[email protected]> > http://knife.lugatgt.org/cgi-bin/mailman/listinfo/mlpack > <http://knife.lugatgt.org/cgi-bin/mailman/listinfo/mlpack> > > > > _______________________________________________ > mlpack mailing list > [email protected] > http://knife.lugatgt.org/cgi-bin/mailman/listinfo/mlpack
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