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From "Weichen Xu (JIRA)" <j...@apache.org>
Subject [jira] [Comment Edited] (SPARK-10078) Vector-free L-BFGS
Date Thu, 12 Jan 2017 04:44:16 GMT

    [ https://issues.apache.org/jira/browse/SPARK-10078?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15819851#comment-15819851
] 

Weichen Xu edited comment on SPARK-10078 at 1/12/17 4:43 AM:
-------------------------------------------------------------

[~debasish83] Can L-BFGS-B be distributed computed when scaled to billions of features in
high efficiency ? If only the interface supporting distributed vector, but internal computation
still use local vector and/or local matrix, then it seems won't make much sense...
Currently VF-LBFGS can turn LBFGS two loop recursion into distributed computing mode, but
the L-BFGS-B seems much more complex then L-BFGS, can it also be computed in parallel ?
I look into L-BFGS-B code in breeze and the core updating Hessian and computing descent direction
in L-BFGS-B is very complex, this part it cannot reuse LBFGS code. So, through which way LBFGS-B
can take advantage of `Vector-free LBFGS` ? 


was (Author: weichenxu123):
[~debasish83] Can L-BFGS-B be distributed computed when scaled to billions of features in
high efficiency ? If only the interface supporting distributed vector, but internal computation
still use local vector and/or local matrix, then it seems won't make much sense...
Currently VF-LBFGS can turn LBFGS two loop recursion into distributed computing mode, but
the L-BFGS-B seems much more complex then L-BFGS, can it also be computed in parallel ?

> 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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