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Posted to issues@spark.apache.org by "Chandan Misra (JIRA)" <ji...@apache.org> on 2018/01/30 14:12:00 UTC

[jira] [Commented] (SPARK-23266) Matrix Inversion on BlockMatrix

    [ https://issues.apache.org/jira/browse/SPARK-23266?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16345083#comment-16345083 ] 

Chandan Misra commented on SPARK-23266:
---------------------------------------

I am one of the authors of the above-mentioned paper. I would like to contribute and help in this regard.

> 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: Critical
>
> 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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