Assume I have an optimization problem:
$$
\min x^TQx
$$
$$
\text{Subject to } Ax \leq b
$$
$$
x \geq 0
$$
$A$ is an $m\times n$ matrix and $x$ is an vector with $n$ elements. I know that it needs $\sqrt{n}\ln(1/\epsilon)$ iterations to converges to an $\epsilon-$acccurate solution. But according to my experience, the converge time also relates to the number of constraints.
My question: How does the number of constraints $m$ influence the convergence time?