[mlpack] GSOC 18 [Mlpack] : Reinforcement learning

[Rohan Raj]

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 <rajrohan1108 at gmail.com> 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 <marcus.edel at fu-berlin.de>
> 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 <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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