[
https://issues.apache.org/jira/browse/SPARK-5563?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14364350#comment-14364350
]
yuhao yang commented on SPARK-5563:
-----------------------------------
Matthew Willson. Thanks for the attention and idea. Apart from Gensim,
vowpal-wabbit also has a distributed implementation provided by Matthew D.
Hoffman, which seems to be amazingly fast. I'll refer to those libraries as
much as possible. And suggestions are always welcome.
> LDA with online variational inference
> -------------------------------------
>
> Key: SPARK-5563
> URL: https://issues.apache.org/jira/browse/SPARK-5563
> Project: Spark
> Issue Type: Improvement
> Components: MLlib
> Affects Versions: 1.3.0
> Reporter: Joseph K. Bradley
> Assignee: yuhao yang
>
> Latent Dirichlet Allocation (LDA) parameters can be inferred using online
> variational inference, as in Hoffman, Blei and Bach. “Online Learning for
> Latent Dirichlet Allocation.” NIPS, 2010. This algorithm should be very
> efficient and should be able to handle much larger datasets than batch
> algorithms for LDA.
> This algorithm will also be important for supporting Streaming versions of
> LDA.
> The implementation will ideally use the same API as the existing LDA but use
> a different underlying optimizer.
> This will require hooking in to the existing mllib.optimization frameworks.
> This will require some discussion about whether batch versions of online
> variational inference should be supported, as well as what variational
> approximation should be used now or in the future.
--
This message was sent by Atlassian JIRA
(v6.3.4#6332)
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org
For additional commands, e-mail: issues-h...@spark.apache.org
