I proposed a similar question involving logarithms, but the problem is about scalar.
I am trying to solve the more generalized form:
$$ \min_{\mathbf{x} \in \mathbb{R}^N_+} \left( \sum_i \left( h_i^T(\mathbf{x}\circ\mathbf{x}) - \mathbf{c_1}\log h_i^T(\mathbf{x}\circ\mathbf{x})\right) + r_1\parallel \mathbf{x} - \mathbf{c_2}\parallel_2^2 \right)$$
where $\mathbf{c_1} \in \mathbb{R}^+$, $\mathbf{c_2} \in \mathbb{R}^N_+$, $h_i \in \mathbb{R}^{N}_+$ is each column of a known matrix, $r_1 \in \mathbb{R}^+$. All are constants.
So, for scalar quadratic eqation, we can find the square root via dividing $(1+r_1)$, but when $1$ is a matrix $H$, how to deal with this form?
But I don't know whether directly extension of scalar quadratic equation is right. Can anyone help me? Thanks in advance!
Edit: formulate the problem to make it clearly.