Proof of convergence theory in optimization

[ianchenmu]

Homework Statement

The question is:


Suppose that lim x_k=x_*, where x_* is a local minimizer of the nonlinear function f. Assume that \triangledown^2 f(x_*) is symmetric positive definite. Prove that the sequence \left \{ f(x_k)-f(x_*) \right \} converges linearly if and only if \left \{ ||x_k-x_*|| \right \} converges linearly. Prove that the two sequences converge at the same rate, regardless of what the rate is. What is the relationship between the rate constant for the two sequences?

Homework Equations

n/a

The Attempt at a Solution

I guess we may use the orthogonal diagonalization of a symmetric matrix and f(x_k)-f(x_*)=\triangledown f(x_*)+\frac{1}{2}(x_k-x_*)^T\cdot\triangledown^2 f(\xi)(x_k-x_*) and \triangledown f(x_*)=0... But I got stuck here. So what's your answer?

 

[Ray Vickson]

Homework Statement

The question is:


Suppose that lim x_k=x_*, where x_* is a local minimizer of the nonlinear function f. Assume that \triangledown^2 f(x_*) is symmetric positive definite. Prove that the sequence \left \{ f(x_k)-f(x_*) \right \} converges linearly if and only if \left \{ ||x_k-x_*|| \right \} converges linearly. Prove that the two sequences converge at the same rate, regardless of what the rate is. What is the relationship between the rate constant for the two sequences?

Homework Equations

n/a

The Attempt at a Solution

I guess we may use the orthogonal diagonalization of a symmetric matrix and f(x_k)-f(x_*)=\triangledown f(x_*)+\frac{1}{2}(x_k-x_*)^T\cdot\triangledown^2 f(\xi)(x_k-x_*) and \triangledown f(x_*)=0... But I got stuck here. So what's your answer?

My answer is that the result you are being asked to prove is wrong.