Comments (4)
First, thing we should reference the cvxpy implementation from that:
https://github.com/cvxgrp/diffcp/blob/ef301811feede5cebb4659598e6b4de822e7a1e0/cpp/src/cones.cpp#L238
It is very similar.
Second, one thing I could not from start is that we a missing a k-=1
because as in the code: # k is the number of negative eigenvalues in X minus ONE
Finally, we should think more about that 1e-4
.
Eigensolver should have larger precision very often (cvxpy even uses 0).
We should consider reducing and having that as a function default parameter.
from mathoptsetdistances.jl.
from mathoptsetdistances.jl.
There is more:
we are not taking advantage of symmetry in unvec_symm
, which could make a difference for eigensolver.
And I haven't seen any correction factor in conversions of matrix to vector form, we might need some sqrt(2)
in some places...
@blegat is the master of that.
from mathoptsetdistances.jl.
seems all good. @joaquimg we should add a performance issue to track the unvec you mentioned above
from mathoptsetdistances.jl.
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from mathoptsetdistances.jl.