chenalong created SPARK-14200:
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Summary: The optimization method of convex function
Key: SPARK-14200
URL: https://issues.apache.org/jira/browse/SPARK-14200
Project: Spark
Issue Type: Question
Components: MLlib, Optimizer
Affects Versions: 2.1.0
Reporter: chenalong
I want to implement Bundle Methods for Regularized Risk Minimization(BMRM) in
Spark MLlib. BMRM is a nonsmooth convex optimization techniques, which is more
faster than SGD and can solve non-differentiable problems and differentiable
problems. Is this idea OK, Can you give me some advices?
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