The link to the paper is: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6137254
I've tried to use look through the code. If you have any opinions on my proposal, please feel free to contact me. I am willing to contribute to this project. Thanks. Best, Zhaoduo 2016-03-14 21:52 GMT+08:00 Ryan Curtin <[email protected]>: > On Sun, Mar 13, 2016 at 05:38:22PM +0800, Zhaoduo WEN wrote: > > Hi, Ryan, > > > > I just knew about GSOC today and I hope it is not late to introduce > myself. > > > > I am Zhaoduo Wen, a senior student from Beijing University of Posts and > > Telecommunications.I've been working on data mining and machine learning > > problems for a year and had some experience on recommender systems. > > > > >From what I know, although collaborative filtering is faster in > prediction > > than matrix factorization framework, either itemKNN collaborative > filtering > > or userKNN collaborative filtering has some drawbacks. One major > > disadvantage is that they suffer from low accuracy since there is > > essentially no knowledge learned about item characteristics so as to > > produce accurate recommendations. However, linear sparse model performs > > better both in prediction accuracy and running time. I have read related > > papers and I was lucky to listen to the author's presentation. > > Consequently, I prefer to using a sparse linear model as the alternatives > > to neighborhood-based collaborative filtering. > > > > I am enthusiastic for contributing to this project as I will be extremely > > excited if I finish this project and someone uses it in future. I once > used > > a library for large linear classification (LIBLINEAR), which has a high > > citation times on google scholar. I was impressed by its fast and > accurate > > performance. I wish I could write one someday. I believe GSOC would be a > > good beginning. > > > > What is your opinion about my proposal? Hope to receive your reply. > Thanks. > > Hi Zhaoduo, > > Can you provide a link to the paper that you are proposing to implement? > > Also, it would be a good idea to take a look through the existing CF > code to see how the sparse linear model you are proposing would fit into > the API. > > Thanks, > > Ryan > > -- > Ryan Curtin | "Leave the gun. Take the cannoli." > [email protected] | - Clemenza > -- Best Regards, Zhaoduo
_______________________________________________ mlpack mailing list [email protected] https://mailman.cc.gatech.edu/mailman/listinfo/mlpack
