Optimization, Mathematics.
‌Better formatted version on ghost (due to Latex support)‌ Consider using gradient descent to minimize a quadratic objective with Hessian $H$. ‌ $$\begin{equation} f(w)=\frac{1}{2}(w-w_*)^TH(w-w_*) \label{loss} \end{equation}$$ ‌ We can specialize by letting $H$ have $i$’th eigenvalue proportional