Gradient method

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

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

with the search directions defined by the gradient of the function at the current point.^{[clarification needed]} Examples of gradient methods are the gradient descent and the conjugate gradient.

See also

References

• Elijah Polak (1997). Optimization : Algorithms and Consistent Approximations. Springer-Verlag. ISBN 0-387-94971-2.

This linear algebra-related article is a stub. You can help Wikipedia by adding missing information.

• v
• t
• e