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Posted to issues@spark.apache.org by "Debasish Das (JIRA)" <ji...@apache.org> on 2014/11/01 03:52:34 UTC
[jira] [Commented] (SPARK-2426) Quadratic Minimization for MLlib
ALS
[ https://issues.apache.org/jira/browse/SPARK-2426?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14192935#comment-14192935 ]
Debasish Das commented on SPARK-2426:
-------------------------------------
Refactored QuadraticMinimizer and NNLS from mllib optimization to breeze.optimize.quadratic
https://github.com/scalanlp/breeze/pull/321
I will update the PR as well but breeze latest depends on scala 2.11 but spark still uses 2.10
All license and copyright information also moved to breeze. So for spark no changes to license/notice files.
> Quadratic Minimization for MLlib ALS
> ------------------------------------
>
> Key: SPARK-2426
> URL: https://issues.apache.org/jira/browse/SPARK-2426
> Project: Spark
> Issue Type: New Feature
> Components: MLlib
> Affects Versions: 1.0.0
> Reporter: Debasish Das
> Assignee: Debasish Das
> Original Estimate: 504h
> Remaining Estimate: 504h
>
> Current ALS supports least squares and nonnegative least squares.
> I presented ADMM and IPM based Quadratic Minimization solvers to be used for the following ALS problems:
> 1. ALS with bounds
> 2. ALS with L1 regularization
> 3. ALS with Equality constraint and bounds
> Initial runtime comparisons are presented at Spark Summit.
> http://spark-summit.org/2014/talk/quadratic-programing-solver-for-non-negative-matrix-factorization-with-spark
> Based on Xiangrui's feedback I am currently comparing the ADMM based Quadratic Minimization solvers with IPM based QpSolvers and the default ALS/NNLS. I will keep updating the runtime comparison results.
> For integration the detailed plan is as follows:
> 1. Add QuadraticMinimizer and Proximal algorithms in mllib.optimization
> 2. Integrate QuadraticMinimizer in mllib ALS
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