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https://issues.apache.org/jira/browse/SPARK-18946?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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zunwen you reopened SPARK-18946:
I have implement a sliceAggregate for RDD, which proform better than
treeAggregate when dimension of
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https://issues.apache.org/jira/browse/SPARK-18946?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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zunwen you closed SPARK-18946.
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Resolution: Duplicate
> treeAggregate will be low effficiency when aggregate high dimension vectors
>
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https://issues.apache.org/jira/browse/SPARK-18946?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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zunwen you updated SPARK-18946:
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Summary: treeAggregate will be low effficiency when aggregate high
dimension vectors in ML algorithm
zunwen you created SPARK-18946:
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Summary: treeAggregate will be low effficiency when aggregate high
dimension vector in ML algorithm
Key: SPARK-18946
URL: https://issues.apache.org/jira/browse/SPARK-18946
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https://issues.apache.org/jira/browse/SPARK-16495?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15432275#comment-15432275
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zunwen you commented on SPARK-16495:
Great, I am looking forward to migrating my ADMM implementation
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https://issues.apache.org/jira/browse/SPARK-16495?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15383477#comment-15383477
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zunwen you commented on SPARK-16495:
I am working on it. I am going to use the implemented ADMM in
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https://issues.apache.org/jira/browse/SPARK-16493?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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zunwen you closed SPARK-16493.
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Resolution: Duplicate
> Add ADMM optimizer in mllib package
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https://issues.apache.org/jira/browse/SPARK-16495?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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zunwen you updated SPARK-16495:
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Description: Alternating Direction Method of Multipliers (ADMM) is well
suited to distributed
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https://issues.apache.org/jira/browse/SPARK-16495?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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zunwen you updated SPARK-16495:
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Description:
Alternating Direction Method of Multipliers (ADMM) is well suited to
distributed
zunwen you created SPARK-16495:
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Summary: Add ADMM optimizer in mllib package
Key: SPARK-16495
URL: https://issues.apache.org/jira/browse/SPARK-16495
Project: Spark
Issue Type: New Feature
zunwen you created SPARK-16493:
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Summary: Add ADMM optimizer in mllib package
Key: SPARK-16493
URL: https://issues.apache.org/jira/browse/SPARK-16493
Project: Spark
Issue Type: New Feature
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