Comment by melony

Why is Newton’s Method not used more often in ML? I know Newton’s method requires the 2nd derivative while Gradient Descent family of algorithms only requires the first, but shouldn’t Newton’s Method be just as straightforward when using autodifferentiation since the process is just a computational graph graph transform using a lookup table?