The optimization problem is： minimize log detP^−1 subject to ||Pu+ buro||\2≤ 1, where P is a semidefinite matrix, buro is Variable, u is known. The code is: using Convex, SCS, LinearAlgebra if VERSION < v"1.2.0-DEV.0" LinearAlgebra.diagm(v::AbstractVector) = diagm(0 => v) end u=rand(3…

\log(\det(A^{-1})) = \log(\frac{1}{\det(A)}) = -\log(\det(A)) :slight_smile:

How to invert variables in the objective of an optimization model

cvanaret April 28, 2021, 9:40am 2

\log(\det(A^{-1})) = \log(\frac{1}{\det(A)}) = -\log(\det(A))

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