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https://issues.apache.org/jira/browse/SPARK-16495?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15431362#comment-15431362
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DB Tsai commented on SPARK-16495:
---------------------------------
This is related to https://issues.apache.org/jira/browse/SPARK-17136 Once we
have a optimizer interface in Spark ML, we can have an implementation of ADMM
optimizer in Spark ML.
> Add ADMM optimizer in mllib package
> -----------------------------------
>
> Key: SPARK-16495
> URL: https://issues.apache.org/jira/browse/SPARK-16495
> Project: Spark
> Issue Type: New Feature
> Components: ML, MLlib
> Reporter: zunwen you
>
> Alternating Direction Method of Multipliers (ADMM) is well suited to
> distributed convex optimization, and in particular to large-scale problems
> arising in statistics, machine learning, and related areas.
> Details can be found in the [S. Boyd's
> paper](http://www.stanford.edu/~boyd/papers/admm_distr_stats.html).
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