[SPARK-2426] Quadratic Minimization for MLlib ALS

• Type: New Feature
• Status: Resolved
• Priority: Major
• Resolution: Won't Fix
• Affects Version/s: 1.4.0
• Component/s: MLlib
• Assignee: Debasish Das
• Reporter: Debasish Das
• Created: 10/Jul/14 00:02
• Updated: 31/Dec/15 09:37
• Resolved: 31/Dec/15 09:37

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

Issue Links

• links to: [Github] Pull Request #3221 (debasish83)
• links to: [Github] Pull Request #5005 (debasish83)