[jira] [Commented] (SPARK-6346) Use faster converging optimization method in MLlib

["Nick Pentreath (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/SPARK-6346?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15682455#comment-15682455 ] 

Nick Pentreath commented on SPARK-6346:
---------------------------------------

I think we can close this ticket? It's pretty old, and everything in {{ml}} that can use L-BFGS now does, yes?

> Use faster converging optimization method in MLlib
> --------------------------------------------------
>
>                 Key: SPARK-6346
>                 URL: https://issues.apache.org/jira/browse/SPARK-6346
>             Project: Spark
>          Issue Type: Improvement
>          Components: ML, MLlib
>            Reporter: Reza Zadeh
>
> According to experiments in SPARK-1503, the LBFGS algorithm converges much faster than our current proximal gradient, which is used throughout MLlib. This ticket is to track replacing slower-converging algorithms, with faster components e.g. LBFGS
> This needs unification of the Optimization interface. For example, the LBFGS implementation should not know about RDDs.



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