(I hope this isn't a RTFM. I saw something in the manual about hermitian matrices related to Lapack, so it only seemed to be dense.)
Is there provision for hermitian *sparse* matrices in Julia, in the sense that if A is "declared" hermitian, only its lower (or upper) triangle is stored and A*x does the right thing? That's always been missing from Matlab, and would be an important feature to have. In smooth optimization, most operators end up being symmetric (e.g., Hessians, or KKT matrices). Thanks.
