Please select all the statements about Newton's method and gradient descent that are correct.多项选择题

Newton’s method typically reaches an optimal solution faster than gradient descent and doesn’t suffer from the issue of slow crawling.

There are no ways to simplify the computation of the Hessian matrix when using Newton’s method.

Both Newton’s method and gradient descent face similar issues when the algorithm encounters a flat region in the objective function.

Newton’s method typically reaches an optimal solution faster than gradient descent, but it suffers from scaling limitations.

Unlike gradient descent, Newton’s method doesn’t need to address numerical stability issues.

Newton’s method typically reaches an optimal solution faster than gradient descent and doesn’t suffer from the zig-zagging behavior commonly observed in gradient descent.