Conjugate Gradient method

1. How does the conjugate gradient method work?
2. Why do we use conjugate gradient method?
3. Why is conjugate gradient method better?
4. Which is true in conjugate gradient method?

How does the conjugate gradient method work?

The conjugate gradient method is a line search method but for every move, it would not undo part of the moves done previously . It optimizes a quadratic equation in fewer step than the gradient ascent. If x is N-dimensional (N parameters), we can find the optimal point in at most N steps.

Why do we use conjugate gradient method?

The conjugate gradient method is a mathematical technique that can be useful for the optimization of both linear and non-linear systems. This technique is generally used as an iterative algorithm, however, it can be used as a direct method, and it will produce a numerical solution.

Why is conjugate gradient method better?

The conjugate gradient method usually converges faster than the steepest descent method. 2. Conjugate directions are computed from gradients of the cost function.

Which is true in conjugate gradient method?

In mathematics, the conjugate gradient method is an algorithm for the numerical solution of particular systems of linear equations, namely those whose matrix is positive-definite.