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From "Apache Spark (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (SPARK-23266) Matrix Inversion on BlockMatrix
Date Thu, 01 Mar 2018 07:10:00 GMT

    [ https://issues.apache.org/jira/browse/SPARK-23266?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16381604#comment-16381604
] 

Apache Spark commented on SPARK-23266:
--------------------------------------

Hello,which version this issue will be release ?

> Matrix Inversion on BlockMatrix
> -------------------------------
>
>                 Key: SPARK-23266
>                 URL: https://issues.apache.org/jira/browse/SPARK-23266
>             Project: Spark
>          Issue Type: New Feature
>          Components: MLlib
>    Affects Versions: 2.2.1
>            Reporter: Chandan Misra
>            Priority: Minor
>
> Matrix inversion is the basic building block for many other algorithms like regression,
classification, geostatistical analysis using ordinary kriging etc. A simple Spark BlockMatrix
based efficient distributed divide-and-conquer algorithm can be implemented using only *6*
multiplications in each recursion level of the algorithm. The reference paper can be found
in
> [https://arxiv.org/abs/1801.04723]



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