verne.freenode.net changed the topic of #mlpack to: http://www.mlpack.org/ -- We don't respond instantly... but we will respond. Give it a few minutes. Or hours. -- Channel logs: http://www.mlpack.org/irc/
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< Prabhat-IIT> rcurtin I've noticed a thing while debugging kmeans that if `initial_centroids` are all equal i.e. all centroids are the same point initially then the result is pure zero i.e all the points are assigned 0 in case of 'allow_empty_clusters` and `kill_empty_clusters` whereas I think in normal mode I doubt points are assigned rather arbitrarily as the training time is almost negligible as compared to the others. Shouldn't we handle t
< rcurtin> Prabhat-IIT: a user using all zeros is a really bad initialization and we do not need to take into account how to handle that since it will cost a lot of extra computation
< Prabhat-IIT> rcurtin: not all zeros but the same point as the centroid of all clusters
< Prabhat-IIT> but yeah its very bad initialization
< Prabhat-IIT> So, I agree with you :)
< Prabhat-IIT> Moreover, after a whole night hardwork I was able to debug the issue in the kmeans test and the issue was that I've to explicitly pass the value of `allow_empty_clusters` as true or false in every test. I don't know why but it is not the case in CLI where this is an optional parameter :(
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< scrcro> I was trying out the RNN.
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< scrcro> Looks like it expects an output for every timestep. Is this true? In my case it does not make sense to have an output for every timestep. I am only interested in the last timestep
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< scrcro> Is there a way to accomplish this?
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< ShikharJ> zoq: You there?
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< zoq> scrcro: I see the problem, one simple solution is to use repmat to modify the responses. But I will keep that in mind and change the class accordingly.
< zoq> ShikharJ: Hello.
< caladrius[m]> zoq: Hi! I have submitted a PR for FReLU. I hope that's fine. Also, I think no work has been done on atrous convolution. Can I take it up then?
< ShikharJ> zoq: Hi, nevermind, I posted my query in one of the PRs I am working on. Please take a look whenever you have some time :)
< zoq> caladrius[m]: Yes please feel free, maybe we can find a way to provide a single convolution class, that handles different ideas, one idea is to use the policy design pattern.
< zoq> ShikharJ: Okay :)
< caladrius[m]> I'll look into that. For the time being, could I implement it as a separate class? I'll merege the two afterwards
< caladrius[m]> *merge
< zoq> caladrius[m]: Yeah, not even sure it's a good idea to merge everything into a single layer.
< caladrius[m]> Yeah, most of the other libraries have it as a separate class.
< caladrius[m]> Also I implemented the huber loss function. I guess it is useful for deep regression and some reinforcement learning applications. Can I submit a PR for that?
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< zoq> caladrius[m]: hm, have to take a look into the function, but my recommendation is to open the PR after the other one.
< caladrius[m]> After atrous convolution, right?
< zoq> yeah
< caladrius[m]> Will do it afterwards then. Thanks!
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