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From "Shivaram Venkataraman (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (SPARK-5256) Improving MLlib optimization APIs
Date Tue, 14 Apr 2015 18:40:12 GMT

    [ https://issues.apache.org/jira/browse/SPARK-5256?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14494562#comment-14494562
] 

Shivaram Venkataraman commented on SPARK-5256:
----------------------------------------------

FWIW I also think that API design is a little orthogonal from implementations / performance
concerns. [~avulanov] While I see your point about overheads, sampling etc. I am not sure
it relates to the API design ?

> Improving MLlib optimization APIs
> ---------------------------------
>
>                 Key: SPARK-5256
>                 URL: https://issues.apache.org/jira/browse/SPARK-5256
>             Project: Spark
>          Issue Type: Umbrella
>          Components: MLlib
>    Affects Versions: 1.2.0
>            Reporter: Joseph K. Bradley
>
> *Goal*: Improve APIs for optimization
> *Motivation*: There have been several disjoint mentions of improving the optimization
APIs to make them more pluggable, extensible, etc.  This JIRA is a place to discuss what API
changes are necessary for the long term, and to provide links to other relevant JIRAs.
> Eventually, I hope this leads to a design doc outlining:
> * current issues
> * requirements such as supporting many types of objective functions, optimization algorithms,
and parameters to those algorithms
> * ideal API
> * breakdown of smaller JIRAs needed to achieve that API
> I will soon create an initial design doc, and I will try to watch this JIRA and include
ideas from JIRA comments.



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