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Posted to issues@spark.apache.org by "Debasish Das (JIRA)" <ji...@apache.org> on 2014/08/13 17:08:12 UTC

[jira] [Updated] (SPARK-2426) Quadratic Minimization for MLlib ALS

     [ https://issues.apache.org/jira/browse/SPARK-2426?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Debasish Das updated SPARK-2426:
--------------------------------

    Description: 
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


  was:
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 ADMM and IPM based QuadraticMinimization solvers to breeze.optimize.quadratic package.
2. Add a QpSolver object in spark mllib optimization which calls breeze
3. Add the QpSolver object in spark mllib ALS



> 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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