On Wed, Apr 04, 2018 at 10:01:11AM +0000, LI Xuran wrote: > Hey Ryan, > > Sorry for the ambiguity. Basically what I did was just a shortlist of > the major past topics related to LRSDP on Github. I didn't realise > that the sparse and dense constraint is already implemented, which is > great. > > By "detail constraints" I basically want to say is that it would be > helpful to have some dataset that is guaranteed to not have any saddle > point, i.e. having only local and global minima so that we can check > the convergence of the LRSDP on problems not involving saddle point. > Maybe it shouldn't be implemented as a constraint but just as > something to keep in mind during the generation of the data. > > since sparse and dense constraints have already been implemented in > MUV SDP then yeah I think a variadic template wouldn't be quite of > help in this case. I haven't give much thought to this over the past > few days as I was caught up with coursework and hackathon, but I will > look further into the code base and give a detailed suggestion on > whether it is possible to further constraint the question or pass on > some useful information to the SDP class this week.
Hi Daniel, I hope the hackathon was enjoyable. Thanks for the clarifications here, I think I understand better now. I think it may be difficult to devise an LRSDP problem that has no saddle points (and prove that it has no saddle points). Thanks, Ryan -- Ryan Curtin | "Bye-bye, goofy woman. I enjoyed repeatedly [email protected] | throwing you to the ground." - Ben Jabituya _______________________________________________ mlpack mailing list [email protected] http://knife.lugatgt.org/cgi-bin/mailman/listinfo/mlpack
