Hello Marcus, I sincerely appreciate your quick respnse.
I would like to mention that I have used CNN in various of my projects. These can easily be found in my github <https://github.com/luffy1996> page. At UIUC, I used my network on top of pretrained alex network. Hence, I have had the flavour of working with CNN before. I sincerely believe that CNN will have positive impact in the problem being discussed. This has already been shown in various atari games which were trained from pixels. I do understand that the working basics of different packages differ significantly . I have experienced this before as I have worked on tensorflow, theano and caffe in past. However what I find is that, the logic behind the implementation is essentially the same. All machine learning packages have been designed to implement the theory of deep learning/machine learning , which is essentially the same. Hence I believe that mlpack is not much different from theano theoretically. Presently, I am going through the codes of mlpack. I had a basic idea of template meta-programming , hence I am comfortable with the codes. I will try to implement the Policy gradient method soon. However I request you to mention if there are any issues which can be resolved now. I would also like to mention that I go by the name of *luffy1996 <https://github.com/luffy1996>*in the irc channel. ᐧ Rohan Raj Department of Chemical Engineering Indian Institute of Technology Guwahati Assam , India Phone : +91 8723990557, +91 8651776581 ᐧ Rohan Raj Department of Chemical Engineering Indian Institute of Technology Guwahati Assam , India Phone : +91 8723990557, +91 8651776581 On 17 February 2018 at 11:59, Rohan Raj <[email protected]> wrote: > Hello Marcus, > > I sincerely appreciate your quick respnse. > > I would like to mention that I have used CNN in various of my projects. > These can easily be found in my github <https://github.com/luffy1996> > page. At UIUC, I used my network on top of pretrained alex network. Hence, I > have had the flavour of working with CNN before. I sincerely believe that > CNN will have positive impact in the problem being discussed. This has > already been shown in various atari games which were trained from pixels. > > I do understand that the working basics of different packages differ > significantly . I have experienced this before as I have worked on > tensorflow, theano and caffe in past. However what I find is that, the > logic behind the implementation is essentially the same. All machine > learning packages have been designed to implement the theory of deep > learning/machine learning , which is essentially the same. Hence I believe > that mlpack is not much different from theano theoretically. > > Presently, I am going through the codes of mlpack. I had a basic idea of > template meta-programming , hence I am comfortable with the codes. I will > try to implement the Policy gradient method soon. However I request you to > mention if there are any issues which can be resolved now. > > I would also like to mention that I go by the name of *luffy1996 > <https://github.com/luffy1996>*in the irc channel. > ᐧ > > Rohan Raj > Department of Chemical Engineering > Indian Institute of Technology Guwahati > Assam , India > Phone : +91 8723990557, +91 8651776581 > > > > On 16 February 2018 at 17:18, Marcus Edel <[email protected]> > wrote: > >> 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 <[email protected]> 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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