2012/3/21 Gael Varoquaux <[email protected]>: > On Wed, Mar 21, 2012 at 12:24:39PM +0900, Mathieu Blondel wrote: >> If the online NMF and SGD-based matrix factorization proposals are >> merged as I suggested before, I think it would make a decent GSOC >> project. Besides, if two different students were to work on the two >> proposals in parallel, I think there would be too much overlap. > > Agreed. In general I think that such a project would have a good profile > for a GSOC. >
Okay, that sounds reasonable to me too. It appears to me that it might be in everyone interest if I apply for a different project. I'm considering "Coordinated descent in linear models beyond squared loss (eg Logistic)" I'm currently working on a p>>N problem using the R scout package, where I’m running into "out of memory" and performance issues due to R's memory restrictions. I could imagine that scikit-learn could really profit I we could get around this problems. In short, I think it could be interesting to implement the scout method too: "We show that ridge regression, the lasso, and the elastic net are special cases of covariance-regularized regression" http://www-stat.stanford.edu/~tibs/ftp/WittenTibshirani2008.pdf Best, Immanuel ------------------------------------------------------------------------------ This SF email is sponsosred by: Try Windows Azure free for 90 days Click Here http://p.sf.net/sfu/sfd2d-msazure _______________________________________________ Scikit-learn-general mailing list [email protected] https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
