mlpack IRC logs, 2018-03-17

Logs for the day 2018-03-17 (starts at 0:00 UTC) are shown below.

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--- Log opened Sat Mar 17 00:00:56 2018
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01:09 < bhairavm> have there been any discussions about the simulator GSOC project?
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04:46 < travis-ci> ShikharJ/mlpack#102 (master - 0e14562 : Ryan Curtin): The build has errored.
04:46 < travis-ci> Change view : https://github.com/ShikharJ/mlpack/compare/1f83394d3300...0e14562937fb
04:46 < travis-ci> Build details : https://travis-ci.org/ShikharJ/mlpack/builds/354618586
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09:32 < zoq> bhairavm: yes checkout the mailing list archive.
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09:55 < travis-ci> ShikharJ/mlpack#103 (ConvolutionalLayer - 2dcdb22 : Shikhar Jaiswal): The build has errored.
09:55 < travis-ci> Change view : https://github.com/ShikharJ/mlpack/commit/2dcdb22749e1
09:55 < travis-ci> Build details : https://travis-ci.org/ShikharJ/mlpack/builds/354661054
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13:05 < thepro> can Adaboost be only used with the decision tree stumps or any other kind of classifiers?
13:07 < rcurtin> thepro: you should be able to use it with any learner that supports instance weights
13:07 < rcurtin> but AdaBoost is generally most successful when used with weaker learners
13:08 < rcurtin> one example of weak learner you could use is the perceptron
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13:55 < Atharva> The readme file in tutorials folder has wrong link to tutorials webpage, in the first line.
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13:59 < yashsharan> hello.If I'm interested in two different ideas should I prepare two proposals or one? I'm interested in reinforcement learning as well as Bidirectional RNN idea for my GSoC project.
14:03 < yashsharan> Also I was wondering for the reinforcement learning idea will the algorithm be implemented only on cartpole and mountain cart environment since these are the only two environment available in mlpack repo?
14:15 < rcurtin> Atharva: can you open an issue or PR for that? I'm not at my desk right now so it's likely I'll forget
14:15 < rcurtin> yashsharan: you can do either, but usually I would suggest that it's better to focus on one proposal instead of two
14:17 < Atharva> rcurtin: I will open a PR
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14:26 < travis-ci> ShikharJ/mlpack#106 (ConvolutionalLayer - 4128d92 : Shikhar Jaiswal): The build has errored.
14:26 < travis-ci> Change view : https://github.com/ShikharJ/mlpack/compare/b746c68fe72d...4128d92aabb6
14:26 < travis-ci> Build details : https://travis-ci.org/ShikharJ/mlpack/builds/354719349
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16:13 < yashsharan> Hello.Is it possible to add Atari game environment from openAI gym? I am doubtful about this because in the source code for atari game environment there is an import atari statement which i think isnt currently present in ml pack
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17:25 < Guest37764> excuse me but how should I identify my username??
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18:27 < sourabhvarshney1> @zoq I am not getting why are there two implementation of rnn in ann codebase? Is this the case that one is due to addition of a layer in a network and other is the implementation of a general rnn?
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18:53 < zoq> yashsharan: You could use https://github.com/zoq/gym_tcp_api, the main purpose of the environments in the codebase is to have something easy to run tests against.
18:55 < zoq> sourabhvars: Hello, you are right, besides adding a layer, the class also preprocesses the input/output pairs for the optimization step.
19:07 < sourabhvarshney1> @zoq I am looking forward to adding brnn and blstm to the codebase this summer. Should I add it like adding blstm in the layer only and brnn both in the layer and as a general method also?
19:09 < zoq> I think RNN class is just fine, that way it will effect any other layer.
19:10 < sourabhvarshney1> I think I can also add one more deep learning module. But I am confused between RBFN and DBN. Can you suggest me one which can be collaborated with these?
19:11 < zoq> collaborated with brnn?
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19:18 < sourabhvarshney1> @zoq Regarding the RNN class. This resolves to just addition of two types of layes of blstm and brnn in ann codebase of mlpack.
19:20 < sourabhvarshney1> @zoq Regarding the collabration. Sorry for the unclear words. I just wanted to know which of these two can be done with brnn and blstm during the time/
19:20 < zoq> sourabhvars: blstm is brrn + lstm
19:20 < zoq> sourabhvars: Ah I see, both.
19:21 < sourabhvarshney1> @zoq Yes. That is what I wanted to say.
19:23 < sourabhvarshney1> I think once brnn is done, blstm can be done quickly. So, I think I can add one more algo. What say @zoq
19:24 < zoq> Agreed, I don't think brnn is enough work for the summer.
19:25 < sourabhvarshney1> So, should I go with brnn with brfn or brnn with dbn. And later can continue with blstm after summer.
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19:35 < qwebirc819267> @zoq I am going with this research paper for brnn: Bidirectional Recurrent Neural Networks by Mike Schuster and Kuldip K. Paliwal. Will this be fine?
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19:37 < sourabhvarshney1> @zoq I am going with this research paper for brnn: Bidirectional Recurrent Neural Networks by Mike Schuster and Kuldip K. Paliwal. Will this be fine?
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19:55 < fsub> hello
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20:11 < sourabhvarshney1> @zoq Searched for rbfn research paper and found: Multivariable Functional Interpolation and Adaptive Networks By Broomhead and Lowe. Should this be used?
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20:28 < zoq> sourabhvars: Yes, both are good to dive in.
20:28 < zoq> fsub: Hello there!
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20:30 < zoq> sourabhvars: Go with the method you like the most, I think both are interesting.
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20:32 < sourabhvarshney1> @zoq I would go with the RBFN. Can you check the papers which I just listed out. Are they fine?
20:33 < zoq> sourabhvars: yes, both are good to dive into the topic.
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20:46 < sourabhvarshney1> Thanks @zoq for help. I would submit the proposal asap.
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22:27 < rf_sust2018> rcurtin: can you please tell me why Cython files are to be generated for python bindings for mlpack befire using SWIG
22:27 < rf_sust2018> *before
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22:58 < rcurtin> rf_sust2018: swig is not being used for mlpack bindingd
22:58 < rcurtin> bindings*
--- Log closed Sun Mar 18 00:00:57 2018