Two type of calculating R in steepest-descent modeling algorithm

1. How do you calculate steepest descent?
2. What are the main components of the steepest descent method?
3. Which of the following method or methods use steepest descent in optimization?
4. What is the major limitation of steepest descent method?

How do you calculate steepest descent?

) = −∇f(xk+1) · f(xk)=0. That is, the Method of Steepest Descent pursues completely independent search directions from one iteration to the next.

What are the main components of the steepest descent method?

In the steepest descent method, there are two important parts, the descent direction and the step size (or how far to descend). The calculations of the exact step size may be very time consuming.

Which of the following method or methods use steepest descent in optimization?

Newton's method is a general approach for solving systems of non-linear equations. Newton's method can conceptually be seen as a steepest descent method, and we will show how it can be applied for convex optimization.

What is the major limitation of steepest descent method?

The main observation is that the steepest descent direction can be used with a different step size than the classical method that can substantially improve the convergence. One disadvantage however is the lack of monotone convergence.