optimization - How to show that the method of steepest descent does not converge in a finite number of steps? - Mathematics Stack Exchange

I have a function, $$f(\mathbf{x})=x_1^2+4x_2^2-4x_1-8x_2,$$ which can also be expressed as $$f(\mathbf{x})=(x_1-2)^2+4(x_2-1)^2-8.$$ I've deduced the minimizer $\mathbf{x^*}$ as $(2,1)$ with $f^*

4. (Steepest Descent) Suppose we seek to minimize

Mathematics, Free Full-Text

Restricted-Variance Constrained, Reaction Path, and Transition State Molecular Optimizations Using Gradient-Enhanced Kriging

Solved I. Solve the following utility maximization problem

Mathematics, Free Full-Text

Data-driven discovery of the governing equations of dynamical systems via moving horizon optimization

Efficient neural codes naturally emerge through gradient descent learning

Sensors, Free Full-Text

A Steepest Descent Method for Set Optimization Problems with Set-Valued Mappings of Finite Cardinality

Stochastic gradient descent for optimization for nuclear systems