ut this
shouldn't be hard.
And currently I don't think any further constraints to the SDP class are needed.
Best Regards
Daniel Li
From: Ryan Curtin <r...@ratml.org>
Sent: 04 April 2018 20:53:52
To: LI Xuran
Cc: mlpack@lists.mlpack.org
Subject: Re: [mlpack]
Curtin <r...@ratml.org>
Sent: 02 April 2018 16:18:17
To: LI Xuran
Cc: mlpack@lists.mlpack.org
Subject: Re: [mlpack] MVU Bug Fix GSOC
On Mon, Mar 26, 2018 at 08:23:20PM +, LI Xuran wrote:
> >I took a quick look at your proposal and I think it is relatively clear
> >and sufficient
Hi Ryan,
>I took a quick look at your proposal and I think it is relatively clear
>and sufficiently detailed. I am not clear on exactly what you mean by
>"5. it might also be useful to write an algorithm to pre-process the
>dataset to make it smoother and convex"---note that the LRSDP
suggestion.
Best Wishes,
Daniel Li
From: LI Xuran
Sent: 18 March 2018 20:15:57
To: mlpack@lists.mlpack.org
Subject: Re: MVU Bug Fix GSOC
Dear Ryan,
I am currently working on my proposal for the Fixes to MVU and low-rank
semidefinite programs and have come up
on that sample
4.(or maybe datasets with a special property such that it should always
converge by an implementation of MVU + LRSDP and check if the expected result
is met )
do you think any of the above ideas worth a try?
Thanks!
Daniel Li
From: LI Xuran
Sent: 17
Hello Ryan,
I am Daniel Li, a second-year student studying Artificial in the University of
Edinburgh. I write fluent c++ code and is interested in taking up the quest to
fix bugs regarding MVU and semidefinite programming in mlpack. I've read about
scalable semidefinite manifold learning and