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From "Dmitriy Lyubimov (JIRA)" <>
Subject [jira] [Updated] (MAHOUT-1365) Weighted ALS-WR iterator for Spark
Date Tue, 26 Nov 2013 00:20:35 GMT


Dmitriy Lyubimov updated MAHOUT-1365:

    Attachment:     (was: distributed-als-with-confidence.pdf)

> Weighted ALS-WR iterator for Spark
> ----------------------------------
>                 Key: MAHOUT-1365
>                 URL:
>             Project: Mahout
>          Issue Type: Task
>            Reporter: Dmitriy Lyubimov
>            Assignee: Dmitriy Lyubimov
>             Fix For: Backlog
> Given preference P and confidence C distributed sparse matrices, compute ALS-WR solution
for implicit feedback (Spark Bagel version).
> Following Hu-Koren-Volynsky method (stripping off any concrete methodology to build C
matrix), with parameterized test for convergence.
> The computational scheme is followsing ALS-WR method (which should be slightly more efficient
for sparser inputs). 
> The best performance will be achieved if non-sparse anomalies prefilitered (eliminated)
(such as an anomalously active user which doesn't represent typical user anyway).
> the work is going here
I am porting away our (A1) implementation so there are a few issues associated with that.

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