I am working on a convex optimization problem that needs to define several (e.g. 5) symmetric matrices as variables. I was wondering if it is possible to define those variables with a single line like
@variable(m, x(N,N,M), Symmetric), where N is the dimension of the matrix, and M is the number of copies of symmetric matrices. Then I can access a symmetric matrix by, e.g.,
From this post (http://ask.cvxr.com/t/semidefinite-relaxations-of-quadratic-constraint/179), it seems to be possible in CVX. So I was thinking it would be nice if I could do similar things in JuMP.