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Posted to issues@spark.apache.org by "Hyukjin Kwon (JIRA)" <ji...@apache.org> on 2019/05/21 04:01:07 UTC

[jira] [Updated] (SPARK-22619) Implement the CG method for ALS

     [ https://issues.apache.org/jira/browse/SPARK-22619?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Hyukjin Kwon updated SPARK-22619:
---------------------------------
    Labels: bulk-closed  (was: )

> Implement the CG method for ALS
> -------------------------------
>
>                 Key: SPARK-22619
>                 URL: https://issues.apache.org/jira/browse/SPARK-22619
>             Project: Spark
>          Issue Type: Improvement
>          Components: ML
>    Affects Versions: 2.2.0
>            Reporter: Nathaniel Wendt
>            Priority: Major
>              Labels: bulk-closed
>
> The conjugate gradient method has been shown to be very efficient at solving the least squares error problem in matrix factorization: http://www.benfrederickson.com/fast-implicit-matrix-factorization/.  Implementing this in Spark could mean a significant speedup in ALS solving as the order of growth is smaller than the default solver (Cholesky).  This has the potential to improve the training phase of collaborative filtering significantly.



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