Here is a minimal example of my problem: I want to find a minimizer x that minimizes the objective function :
opnorm(A*x-b,2)^2
I tried Convex.jl, but it doesn’t work for the operator norm.
Here is a minimal example of my problem: I want to find a minimizer x that minimizes the objective function :
opnorm(A*x-b,2)^2
I tried Convex.jl, but it doesn’t work for the operator norm.
If x
and b
are 1d arrays, this is not defined in Julia. If they are 1-column matrices, this is equivalent to the Euclidean norm. What are the dimensions here?
Thank you for your reply!
Let’s say A is d by n, x is n-dimensional and b is d-dimensional, which means A*x-b is d-dimensional.
opnorm
is for operators (matrices), which I think is what @stevengj is getting at here. Do you mean norm
instead?