Given a fat matrix $B \in \mathbb{C}^{n \times m}$ (where $m > n$) with full row rank, I would like to find (numerically) a full-rank matrix $A$ that minimizes the Frobenius norm of the product $A B$. Formally,
$$\underset{A \in \mathbb{C}^{n \times n}}{\text{minimize}} \quad \frac{1}{2} \|AB\|_F^2 \quad \text{subject to} \quad \det (A) \neq 0$$
The value of $m$ is typically an order of magnitude larger than $n$. The sizes ($n,m$) I am interested in may be on the order of hundreds.
I have found the following discussion, which I guess could be generalized to the above case. I wonder if there is a simpler solution in this particular scenario.