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From "Debasish Das (JIRA)" <j...@apache.org>
Subject [jira] [Comment Edited] (SPARK-10078) Vector-free L-BFGS
Date Tue, 03 Jan 2017 00:26:58 GMT

    [ https://issues.apache.org/jira/browse/SPARK-10078?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15793760#comment-15793760
] 

Debasish Das edited comment on SPARK-10078 at 1/3/17 12:26 AM:
---------------------------------------------------------------

Ideally feature partitioning should be automatically tuned...at 100M features master only
processing what we do with Breeze LBFGS / OWLQN will also get benefitted  by VL-BFGS....Ideally
it should be part of breeze and a proper interface should be defined so that the Breeze VL-BFGS
solver can be called in Spark ML...There are bounded BFGS that's in breeze...all of them will
be benefited by this change. A solver can be used in other frameworks as well and may not
be constrained to RDD if possible...


was (Author: debasish83):
Ideally feature partitioning should be automatically tuned...at 100M features master only
processing what we do with Breeze LBFGS / OWLQN will also get benefitted  by VL-BFGS....Ideally
it should be part of breeze and a proper interface should be defined so that the Breeze VL-BFGS
solver can be called in Spark ML...

> Vector-free L-BFGS
> ------------------
>
>                 Key: SPARK-10078
>                 URL: https://issues.apache.org/jira/browse/SPARK-10078
>             Project: Spark
>          Issue Type: New Feature
>          Components: ML
>            Reporter: Xiangrui Meng
>            Assignee: Yanbo Liang
>
> This is to implement a scalable version of vector-free L-BFGS (http://papers.nips.cc/paper/5333-large-scale-l-bfgs-using-mapreduce.pdf).
> Design document:
> https://docs.google.com/document/d/1VGKxhg-D-6-vZGUAZ93l3ze2f3LBvTjfHRFVpX68kaw/edit?usp=sharing



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