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  1. Spark
  2. SPARK-2426

Quadratic Minimization for MLlib ALS

    Details

    • Type: New Feature
    • Status: Resolved
    • Priority: Major
    • Resolution: Won't Fix
    • Affects Version/s: 1.4.0
    • Fix Version/s: None
    • Component/s: MLlib
    • Labels:
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      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

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            • Assignee:
              debasish83 Debasish Das
              Reporter:
              debasish83 Debasish Das
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