Thanks I just saw.
I'll give it a read tomorrow.

Andy


On 03/23/2015 08:09 PM, Wei Xue wrote:
Hi Andreas,

I have submitted my updated proposal as well.


Thanks!
Wei Xue
​

On Mon, Mar 16, 2015 at 4:36 PM, Andreas Mueller <t3k...@gmail.com <mailto:t3k...@gmail.com>> wrote:

    Hi Wei Xue.
    I am also not very convinced by the core-set approach.
    I'd rather focus on improving the API and fixing issues in the
    VBGMM and DPGMM.
    I was hoping that Murphy's book has some more details on DPGMM,
    but I didn't find any yet. He doesn't seem to talk about
    variational inference in Dirichlet processes.

    So far I think your proposal looks solid.
    It would be great if you could work on some pull requests to
    support your application.

    Best,
    Andy



    On 03/16/2015 04:23 PM, Wei Xue wrote:
    Hi groups,

    I am a PhD student in Florida International University, US. I am
    interested in the topic improving GMM. I draft a proposal for
    this topic.
    
https://github.com/xuewei4d/scikit-learn/wiki/GSoC-2015-Proposal:-Improve-GMM

    Here are some questions I would like to discuss.

    1. -1 for coreset. The
    paper(http://las.ethz.ch/files/feldman11scalable-long.pdf) is new
    and its citations less than 15. The application situations are on
    clusters, streaming data, which is (I think) is rare for
    scikit-learn.

    2. Currently, I have gone over the Approximation Inference
    chapter in PRML (Bishop's machine learning book) and Blei's 2006
    paper. But I have not dig much into the code, so I don't have a
    detailed reimplement plan yet. Do I need to add more details into
    the 'Theory and Implementation' part of the proposal?

    3. Any feedback is welcome.

    Thanks,
    Wei Xue


    
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