Let's say we have a smooth function $f:\mathbb{R}^{1000000} \rightarrow \mathbb{R}$, which we want to minimize using a method from numerical optimization. which method would we choose? Is the conjugate gradient method the best choice? What methods are better than others in the minimization process of high-dimensional problems?
Thank you very much for your time!