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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