[mlpack-git] [mlpack] Low-rank constraint matrices in LRSDP (#578)

[Evan Patterson]

Upon further thought, I do think there is an important reason to handle classes of constraints differently, as in the template approach: the optimal order of the calculations depends on the type of the constraint. When computing `L = 2*S*R`, with dense constraints you want to sum `S` first then multiply `S*R` (as is done currently), while with rank-1 constraints you compute each `a a^T R` efficiently and then sum.



---
You are receiving this because you are subscribed to this thread.
Reply to this email directly or view it on GitHub:
https://github.com/mlpack/mlpack/issues/578#issuecomment-197555168
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <https://mailman.cc.gatech.edu/pipermail/mlpack-git/attachments/20160316/5886cecf/attachment.html>