Denote the function as $f(x)$, $g$ is the gradient and $H$ is is the Hessian at $x^{(0)}$. We calculate the new point $x = x^{(0)} - \epsilon g$. We can obtian that $f(x^{(0)} - \epsilon g) \approx f(x^{(0)}) - \epsilon g^Tg + \frac{1}{2} \epsilon^2 g^THg$ According to the above equation, the optimal step size when $g^THg$ is positive is $\epsilon^* = \frac{g^Tg}{g^THg}$