On Fri, Mar 16, 2018 at 08:18:10PM +0530, Manish Kumar wrote: > Thanks Ryan for helping me out. I got little anxious by learning the fact > that LMNN+LRSDP may not work and was thinking that my GSoC project may go > futile. > > I do want to continue LMNN+LRSDP. I also see a good opportunity to do > something new while working on LMNN+LRSDP and that's why I never planned to > leave it but was looking for a perfect time for a project like this. > > I will stick to the proposal and will try to achieve the results. > > I just want to propose a little modification to the proposal. Tell me, if > that sounds fair. > I went through BoostMetric literature and find it as a significant > improvement over LMNN. So, can we at least include BoostMetric as a part of > the project apart from LMNN. I am sure that it will be a pretty good > addition and currently except author's implementation there is no other > implementation out there. Moreover, existing implementation takes the > exponential loss into consideration and we may include implementation based > on logistic loss function which shows improvement over the exponential one. > If that's okay, I will make some small changes to timeline and proposal. > This way we could have some pretty awesome metric learning algorithms.
That sounds reasonable to me. I think that BoostMetric is a generalization of LMNN, so maybe through some clever templatization you can support the other components. I haven't read the paper in detail though so I am not fully sure. -- Ryan Curtin | "Do they hurt?" [email protected] | - Jessica 6 _______________________________________________ mlpack mailing list [email protected] http://knife.lugatgt.org/cgi-bin/mailman/listinfo/mlpack
