[jira] [Closed] (FLINK-1965) Implement the Orthant-wise Limited Memory QuasiNewton optimization algorithm, a variant of L-BFGS that handles L1 regularization

["Chesnay Schepler (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/FLINK-1965?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Chesnay Schepler closed FLINK-1965.
-----------------------------------
    Resolution: Won't Do

Closing since flink-ml is effectively frozen.

> Implement the Orthant-wise Limited Memory QuasiNewton optimization algorithm, a variant of L-BFGS that handles L1 regularization
> --------------------------------------------------------------------------------------------------------------------------------
>
>                 Key: FLINK-1965
>                 URL: https://issues.apache.org/jira/browse/FLINK-1965
>             Project: Flink
>          Issue Type: Wish
>          Components: Library / Machine Learning
>            Reporter: Theodore Vasiloudis
>            Priority: Minor
>              Labels: ML
>
> The Orthant-wise Limited Memory QuasiNewton (OWL-QN) is a quasi-Newton optimization method similar to L-BFGS that can handle L1 regularization. 
> Implementing this would allow us to obtain sparse solutions while at the same time having the convergence benefits of a quasi-Newton method, when compared to stochastic gradient descent.
> [Link to paper|http://research-srv.microsoft.com/en-us/um/people/jfgao/paper/icml07scalable.pdf]
> [Link to example implementation|http://research.microsoft.com/en-us/downloads/b1eb1016-1738-4bd5-83a9-370c9d498a03/]



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