ChanServ changed the topic of #mlpack to: "mlpack: a fast, flexible machine learning library :: We don't always respond instantly, but we will respond; please be patient :: Logs at http://www.mlpack.org/irc/
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< krishna> Respected sir,
< krishna> I am a B.Tech student in Computer Science and Engineering from India
< krishna> Previously I have been looking into mlpack organisation from different source like github
< krishna> after going through it I wish to contribute to this open source organisation
< krishna> any input I can get regarding this?
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< krishna> I wish to contribute by adding a differential evolution algorithm to the existing mlpack libraries. Can that be an effective addition to it?
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< jenkins-mlpack2> Project docker mlpack nightly build build #196: STILL UNSTABLE in 3 hr 39 min: http://ci.mlpack.org/job/docker%20mlpack%20nightly%20build/196/
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< zoq> krishna: Hello, sure, the methods should probably be part of the ensmallen repo: https://github.com/mlpack/ensmallen
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< rcurtin> zoq: "on a compiler journey" :) I like it :)
< zoq> rcurtin: Still fighting with some mingw64+windows constraints ...
< rcurtin> not an easy journey I suppose :)
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< zoq> somebody posted a link to ensmallen in the in R subreddit https://www.reddit.com/r/cpp/comments/aicl4h/ensmallen_a_headeronly_c_library_for_mathematical/
< rcurtin> lots of people misunderstanding why someone would use C++ in that thread
< zoq> not the first time I see the discussion about armadillo and autodiff
< ShikharJ> Hmm, I've been looking at the comments, and they really seem to be interested in an autodiff solver. Might be a good project for GSoC?
< rcurtin> I feel like it would be a huge amount of maintenance. but, one thing that might be useful is seeing if ensmallen could use some existing C++ autodiff package
< zoq> Agreed, getting autodiff right is a huge effort, not sure GSoC is a good fit for such a project.
< ShikharJ> That could be a good option too.
< rcurtin> it's probably enough work to get some autodiff package working with ensmallen and then write up tutorials and documentation for it, I suspect :)
< rcurtin> one of the important things will be benchmarking, since often autodiff implementations can be slower
< zoq> right, I think the paper has some compelling numbers in that direction
< ShikharJ> Some people also seem to be concerned with the non-use of Eigen and the compile times for ensmallen. How big of an issue is that?
< ShikharJ> I didn't see compile times reduce by much when we shifted ensmallen to a separate repository, so I think it might be safe to assume that it doesn't lead to a huge compile time overhead?
< rcurtin> if you're driven to using C++ for your application, it's likely that compile time doesn't really matter all that much
< rcurtin> certainly compiling some program that uses ensmallen will increase the compile time, but not by too much more than what Armadillo already does
< rcurtin> I don't understand everyone's focus on Eigen instead of Armadillo either. sure, it's what TensorFlow used... but the syntax for Armadillo is so much nicer
< rcurtin> and the fact that it wraps any LAPACK/BLAS is, in my opinion, a better thing than hand-implemented BLAS like Eigen did
< rcurtin> but... I realize that I have a biased perspective :)
< ShikharJ> Hmm, I have to agree that Armadillo's source code has got to be the most beautiful piece of code I have seen in a long time.