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https://issues.apache.org/jira/browse/SPARK-23266?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Sean Owen updated SPARK-23266:
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Priority: Minor (was: Critical)
When do you need to invert a matrix vs just solve a linear system? the latter
is typically faster and more stable. I know you give examples here but can you
be more specific about applications and define kriging?
> 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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