[jira] [Commented] (SYSTEMML-751) Support functions as arguments

["Manoj Kumar (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/SYSTEMML-751?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15314620#comment-15314620 ] 

Manoj Kumar commented on SYSTEMML-751:
--------------------------------------

Related: https://issues.apache.org/jira/browse/SYSTEMML-726 

> Support functions as arguments
> ------------------------------
>
>                 Key: SYSTEMML-751
>                 URL: https://issues.apache.org/jira/browse/SYSTEMML-751
>             Project: SystemML
>          Issue Type: Wish
>            Reporter: Manoj Kumar
>
> Hi,
> How difficult is it to support functions as arguments? (If not done already)
> One real use-case would be to just implement a modular lbfgs, newton-cg etc as in (http://docs.scipy.org/doc/scipy/reference/generated/scipy.optimize.fmin.html#scipy.optimize.fmin)
> I believe this lessens burden on code maintenance and brings in new users, because every time I implement a new algorithm, I just need to check that my function (and gradient) implementation is correct.
> I ultimately would like to do this.
> source("lbfgs.dml") as lbfgs
> f = loss_function() {
> }
> w_init = B = matrix(“0”, rows = 1, cols = 10)
> w = lbfgs::optimize(w_init, f)



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