Gradient method

 ( First Order Methods ) 

In optimization, a gradient method is an algorithm to solve problems of the form

$\backslash min\_\{x\backslash in\backslash mathbb\; R^n\}\backslash ;\; f(x)$

with the search directions defined by the gradient of the function at the current point. Examples of gradient methods are the gradient descent and the conjugate gradient.

---

See also

• Gradient descent
• Stochastic gradient descent
• Coordinate descent
• Frank–Wolfe algorithm
• Landweber iteration
• Random coordinate descent
• Conjugate gradient method
• Derivation of the conjugate gradient method
• Nonlinear conjugate gradient method
• Biconjugate gradient method
• Biconjugate gradient stabilized method

• Elijah Polak (1997). 9780387949710, Springer-Verlag. ISBN 9780387949710

Post Comment